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c3b05b12-44ef-4440-95cd-47dbad75c6d1 | completed | 2025-01-16T03:09:40.503498 | 2025-01-19T18:57:44.897588 | 512a21c2-5f63-40b2-8985-c806130eaa64 | Welcome aMUSEd: Efficient Text-to-Image Generation | Isamu136, valhalla, williamberman, sayakpaul | amused.md | 
We’re excited to present an efficient non-diffusion text-to-image model named **aMUSEd**. It’s called so because it’s a open reproduction of [Google's MUSE](https://muse-model.github.io/). aMU... | [
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34e8d3d2-8d44-4a88-8792-d119897bc887 | completed | 2025-01-16T03:09:40.503515 | 2025-01-19T19:15:16.732681 | 176c95b8-d03a-4021-9066-443c7afabc02 | TTS Arena: Benchmarking Text-to-Speech Models in the Wild | mrfakename, reach-vb, clefourrier, Wauplin, ylacombe, main-horse, sanchit-gandhi | arena-tts.md | Automated measurement of the quality of text-to-speech (TTS) models is very difficult. Assessing the naturalness and inflection of a voice is a trivial task for humans, but it is much more difficult for AI. This is why today, we’re thrilled to announce the TTS Arena. Inspired by [LMSys](https://lmsys.org/)'s [Chatbot A... | [
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4b6cb936-4d75-460a-b167-e63c660fb954 | completed | 2025-01-16T03:09:40.503523 | 2025-01-19T17:19:24.171899 | e9fa7665-0a69-4297-9803-560e44a97fcd | 'Welcome Stable-baselines3 to the Hugging Face Hub 🤗' | ThomasSimonini | sb3.md | At Hugging Face, we are contributing to the ecosystem for Deep Reinforcement Learning researchers and enthusiasts. That’s why we’re happy to announce that we integrated [Stable-Baselines3](https://github.com/DLR-RM/stable-baselines3) to the Hugging Face Hub.
[Stable-Baselines3](https://github.com/DLR-RM/stable-baselin... | [
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53d74d95-9179-4a7e-9503-9ef849ea5b5f | completed | 2025-01-16T03:09:40.503530 | 2025-01-16T15:13:38.898087 | 74b8bc6a-692c-416c-b570-0348acc65937 | Evaluating Audio Reasoning with Big Bench Audio | mhillsmith, georgewritescode | big-bench-audio-release.md | The emergence of native Speech to Speech models offers exciting opportunities to increase voice agent capabilities and simplify speech-enabled workflows. However, it's crucial to evaluate whether this simplification comes at the cost of model performance or introduces other trade-offs.
To support analysis of this, Art... | [
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d756afb7-fb3d-45b6-a6ed-f3c0b2aca33d | completed | 2025-01-16T03:09:40.503537 | 2025-01-19T17:16:42.246545 | 0ebf00db-0d64-4453-8d0c-46ff249f6216 | Active Learning with AutoNLP and Prodigy | abhishek | autonlp-prodigy.md | Active learning in the context of Machine Learning is a process in which you iteratively add labeled data, retrain a model and serve it to the end user. It is an endless process and requires human interaction for labeling/creating the data. In this article, we will discuss how to use [AutoNLP](https://huggingface.co/au... | [
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bc4d0125-a71d-4d9d-b0bc-d0c2f3e5f55d | completed | 2025-01-16T03:09:40.503545 | 2025-01-16T13:32:38.357937 | cda6b46c-5b8b-4953-bed6-201f660a9851 | CyberSecEval 2 - A Comprehensive Evaluation Framework for Cybersecurity Risks and Capabilities of Large Language Models | r34p3r1321, csahana95, liyueam10, cynikolai, dwjsong, simonwan, fa7pdn, is-eqv, yaohway, dhavalkapil, dmolnar, spencerwmeta, jdsaxe, vontimitta, carljparker, clefourrier | leaderboard-llamaguard.md | With the speed at which the generative AI space is moving, we believe an open approach is an important way to bring the ecosystem together and mitigate potential risks of Large Language Models (LLMs). Last year, Meta released an initial suite of open tools and evaluations aimed at facilitating responsible development... | [
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2725e9e4-bf5b-404b-81ea-65608c67ae31 | completed | 2025-01-16T03:09:40.503551 | 2025-01-16T03:25:04.370952 | 9ce6e0ed-631e-422c-a5f6-c827a389dca6 | Yes, Transformers are Effective for Time Series Forecasting (+ Autoformer) | elisim, kashif, nielsr | autoformer.md | <script async defer src="https://unpkg.com/medium-zoom-element@0/dist/medium-zoom-element.min.js"></script>
<a target="_blank" href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/autoformer-transformers-are-effective.ipynb">
<img src="https://colab.research.google.com/assets/col... | [
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9e07b7d0-6dda-4d46-9309-34f5b37df5fa | completed | 2025-01-16T03:09:40.503555 | 2025-01-19T17:18:04.994114 | 2b80e1db-ce18-4936-9d9e-cd1d68eef81e | DuckDB: analyze 50,000+ datasets stored on the Hugging Face Hub | stevhliu, lhoestq, severo | hub-duckdb.md | The Hugging Face Hub is dedicated to providing open access to datasets for everyone and giving users the tools to explore and understand them. You can find many of the datasets used to train popular large language models (LLMs) like [Falcon](https://huggingface.co/datasets/tiiuae/falcon-refinedweb), [Dolly](https://hug... | [
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6810fa31-a3fc-441f-ab65-5bc7398dfd6a | completed | 2025-01-16T03:09:40.503560 | 2025-01-16T13:33:10.791677 | b2fd032a-6206-49ee-9bf6-968128291986 | Introduction to ggml | ngxson, ggerganov, slaren | introduction-to-ggml.md | [ggml](https://github.com/ggerganov/ggml) is a machine learning (ML) library written in C and C++ with a focus on Transformer inference. The project is open-source and is being actively developed by a growing community. ggml is similar to ML libraries such as PyTorch and TensorFlow, though it is still in its early stag... | [
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324207b3-82f5-4ce6-b459-1e518d0c41d6 | completed | 2025-01-16T03:09:40.503565 | 2025-01-16T03:23:21.501443 | 82b9ba76-bb6d-44a9-a8b4-7825a4bc874a | License to Call: Introducing Transformers Agents 2.0 | m-ric, lysandre, pcuenq | agents.md | ## TL;DR
We are releasing Transformers Agents 2.0!
⇒ 🎁 On top of our existing agent type, we introduce two new agents that **can iterate based on past observations to solve complex tasks**.
⇒ 💡 We aim for the code to be **clear and modular, and for common attributes like the final prompt and tools to be transparen... | [
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089f6c1f-a78b-46ef-8001-15039300aaa4 | completed | 2025-01-16T03:09:40.503570 | 2025-01-16T15:09:46.810568 | 805b8672-5c1e-47cf-a66a-0213c39de30c | Releasing Outlines-core 0.1.0: structured generation in Rust and Python | bwillard, drbh, erikkaum, kc611, remi, umut-sahin, willkurt | outlines-core.md | - Speed: Users can expect to see an 2x improvement in index compilation.
- Separation of Concerns: It's now easier to incorporate structured generation into other libraries. `outlines-core` is very lightweight.
- Portability: Having core algorithms in Rust allows binding for languages other than Python.
These improvem... | [
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5b2f9ea7-53b4-4cd9-b6ca-72b8b0c8411d | completed | 2025-01-16T03:09:40.503575 | 2025-01-19T17:08:01.422646 | 1786c50b-4818-433b-8d39-7dd204de16da | Accelerating Protein Language Model ProtST on Intel Gaudi 2 | juliensimon, Jiqing, Santiago Miret, katarinayuan, sywangyi, MatrixYao, ChrisAllenMing, kding1 | intel-protein-language-model-protst.md | <p align="center">
<img src="assets/intel-protein-language-model-protst/01.jpeg" alt="A teenage scientist creating molecules with computers and artificial intelligence" width="512"><br>
</p>
## Introduction
Protein Language Models (PLMs) have emerged as potent tools for predicting and designing protein structure and... | [
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4209c3e5-c8f3-4a5a-beb9-0ef0145fa236 | completed | 2025-01-16T03:09:40.503580 | 2025-01-19T19:07:01.209870 | 125d503d-a16f-481f-a912-c0e0a2cf1c9f | Opinion Classification with Kili and HuggingFace AutoTrain | alperiox | opinion-classification-with-kili.md | ## Introduction
Understanding your users’ needs is crucial in any user-related business. But it also requires a lot of hard work and analysis, which is quite expensive. Why not leverage Machine Learning then? With much less coding by using Auto ML.
In this article, we will leverage [HuggingFace AutoTrain](https://hug... | [
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46889eed-1e57-45db-8caf-04f85d167bd1 | completed | 2025-01-16T03:09:40.503585 | 2025-01-19T18:49:27.581331 | 57ddc46a-9421-48dd-8d06-797c96e3ef52 | Machine Learning Experts - Margaret Mitchell | britneymuller | meg-mitchell-interview.md | Hey friends! Welcome to Machine Learning Experts. I'm your host, Britney Muller and today’s guest is none other than [Margaret Mitchell](https://twitter.com/mmitchell_ai) (Meg for short). Meg founded & co-led Google’s Ethical AI Group, is a pioneer in the field of Machine Learning, has published over 50 papers, and is ... | [
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b2a95f28-c3ed-415d-b9c4-4134abba5ad0 | completed | 2025-01-16T03:09:40.503590 | 2025-01-19T18:47:00.885314 | 16d39d94-9482-4880-97d3-40a977b2d8cf | Optimizing your LLM in production | patrickvonplaten | optimize-llm.md | <a target="_blank" href="https://colab.research.google.com/github/patrickvonplaten/notebooks/blob/master/Getting_the_most_out_of_LLMs.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
***Note***: *This blog post is also available as a documentation page on [Tran... | [
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d65fb5c8-20e9-447a-8dcf-0903396ef54c | completed | 2025-01-16T03:09:40.503594 | 2025-01-16T13:33:56.864559 | 10e0f404-fb12-4353-aa3e-1d4da8f98b00 | Improving Prompt Consistency with Structured Generations | willkurt, remi, clefourrier | evaluation-structured-outputs.md | Recently, the *Leaderboards and Evals* research team at Hugging Face did small experiments, which highlighted how fickle evaluation can be. For a given task, results are extremely sensitive to minuscule changes in prompt format! However, this is not what we want: a model prompted with the same amount of information as ... | [
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b68901fc-5aad-4cca-adbd-d0f667288d1c | completed | 2025-01-16T03:09:40.503599 | 2025-01-16T14:19:17.368723 | 7fe03952-b8e4-4155-a9ef-454788f2da2d | Deploy Meta Llama 3.1 405B on Google Cloud Vertex AI | alvarobartt, philschmid, pagezyhf, jeffboudier | llama31-on-vertex-ai.md | [Meta Llama 3.1](https://huggingface.co/blog/llama31) is the latest open LLM from Meta, released in July 2024. Meta Llama 3.1 comes in three sizes: 8B for efficient deployment and development on consumer-size GPU, 70B for large-scale AI native applications, and 405B for synthetic data, LLM as a Judge or distillation; a... | [
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07f9587d-5176-4d34-bc86-6430cfcc85ac | completed | 2025-01-16T03:09:40.503604 | 2025-01-19T17:15:51.889569 | b192380a-166c-4b33-9c8f-bf2cd9746aa1 | Letting Large Models Debate: The First Multilingual LLM Debate Competition | xuanricheng, lilaczheng, xiyang99, Yonghua, philokey, xuejing2409, graykingw, daiteng01, eyuansu71, Lyfly2024, xianbao, clefourrier | debate.md | Current static evaluations and user-driven arenas have exhibited their limitations and biases in the previous year. Here, we explore a novel way to evaluate LLMs: debate.
Debate is an excellent way to showcase reasoning strength and language abilities, used all across history, from the debates in the Athenian Ecclesia ... | [
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3ee44311-992b-4edb-8486-78ecd8eb66c9 | completed | 2025-01-16T03:09:40.503609 | 2025-01-19T19:13:47.626374 | a91d9ad3-d678-4310-bf87-19d698dd151e | The Technology Behind BLOOM Training | stas | bloom-megatron-deepspeed.md | In recent years, training ever larger language models has become the norm. While the issues of those models' not being released for further study is frequently discussed, the hidden knowledge about how to train such models rarely gets any attention. This article aims to change this by shedding some light on the technol... | [
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18dbf9d9-289a-4fbf-8178-ac6337ca6f9e | completed | 2025-01-16T03:09:40.503614 | 2025-01-19T19:02:59.902523 | c14e44a0-202e-4d30-915e-758603cee1ac | Let's talk about biases in machine learning! Ethics and Society Newsletter #2 | yjernite | ethics-soc-2.md | _Bias in ML is ubiquitous, and Bias in ML is complex; so complex in fact that no single technical intervention is likely to meaningfully address the problems it engenders. ML models, as sociotechnical systems, amplify social trends that may exacerbate inequities and harmful biases in ways that depend on their deploymen... | [
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469c095e-3775-43c2-a559-6b60e2ecfebc | completed | 2025-01-16T03:09:40.503619 | 2025-01-16T03:14:23.309388 | b7b8e69d-5b06-4717-930a-8004289414c2 | What's going on with the Open LLM Leaderboard? | clefourrier, SaylorTwift, slippylolo, thomwolf | open-llm-leaderboard-mmlu.md | Recently an interesting discussion arose on Twitter following the release of [**Falcon 🦅**](https://huggingface.co/tiiuae/falcon-40b) and its addition to the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard), a public leaderboard comparing open access large language models.
The ... | [
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24cbe918-55df-4b4c-9e4e-275022ec4e28 | completed | 2025-01-16T03:09:40.503624 | 2025-01-16T15:15:11.628138 | d86b9a33-21b5-4301-aae8-91773f9c3794 | Rocket Money x Hugging Face: Scaling Volatile ML Models in Production | nicokuzak, ccpoirier | rocketmoney-case-study.md | #### "We discovered that they were not just service providers, but partners who were invested in our goals and outcomes” _- Nicolas Kuzak, Senior ML Engineer at Rocket Money._
## Scaling and Maintaining ML Models in Production Without an MLOps Team
We created [Rocket Money](https://www.rocketmoney.com/) (a personal f... | [
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36312351-e13c-4242-a2c8-caacb149d447 | completed | 2025-01-16T03:09:40.503628 | 2025-01-19T19:14:35.620296 | 6ae008b5-5cdc-4b03-9476-8539385e917e | Accelerate BERT inference with Hugging Face Transformers and AWS Inferentia | philschmid | bert-inferentia-sagemaker.md | <script async defer src="https://unpkg.com/medium-zoom-element@0/dist/medium-zoom-element.min.js"></script>
notebook: [sagemaker/18_inferentia_inference](https://github.com/huggingface/notebooks/blob/master/sagemaker/18_inferentia_inference/sagemaker-notebook.ipynb)
The adoption of [BERT](https://huggingface.co/blog... | [
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acc2c571-0b94-4d96-9281-b9343b762a08 | completed | 2025-01-16T03:09:40.503633 | 2025-01-19T19:05:49.051676 | 8e4030bc-06d6-40fe-bb17-cd7c4040a34d | Introducing the Data Measurements Tool: an Interactive Tool for Looking at Datasets | sasha, yjernite, meg | data-measurements-tool.md | ***tl;dr:*** We made a tool you can use online to build, measure, and compare datasets.
[Click to access the 🤗 Data Measurements Tool here.](https://huggingface.co/spaces/huggingface/data-measurements-tool) | [
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2fa892f1-5700-4436-816a-2f93af7df6ac | completed | 2025-01-16T03:09:40.503638 | 2025-01-19T19:00:44.085570 | 3552af13-8db9-4fe5-876d-ff77d1c56252 | Ryght’s Journey to Empower Healthcare and Life Sciences with Expert Support from Hugging Face | andrewrreed, johnnybio | ryght-case-study.md | > [!NOTE] This is a guest blog post by the Ryght team.
## Who is Ryght?
Ryght is building an enterprise-grade generative AI platform tailored for the healthcare and life sciences sectors. Today is their official launch of [Ryght Preview](https://www.ryght.ai/signup?utm_campaign=Preview%20Launch%20April%2016%2C%2024&u... | [
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e235c88b-b423-47da-981d-e36926480d38 | completed | 2025-01-16T03:09:40.503642 | 2025-01-16T03:25:43.027962 | 48ea74a4-bb4e-4978-b87c-2e69ebbc18b3 | Constitutional AI with Open LLMs | vwxyzjn, lewtun, edbeeching, lvwerra, osanseviero, kashif, thomwolf | constitutional_ai.md | Since the launch of ChatGPT in 2022, we have seen tremendous progress in LLMs, ranging from the release of powerful pretrained models like [Llama 2](https://arxiv.org/abs/2307.09288) and [Mixtral](https://mistral.ai/news/mixtral-of-experts/), to the development of new alignment techniques like [Direct Preference Optimi... | [
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90722a1f-31d3-4502-a635-b2343c7ac493 | completed | 2025-01-16T03:09:40.503647 | 2025-01-19T18:57:35.679671 | d73bb422-b1ff-463d-af74-44efa1d896fa | Introducing Optimum: The Optimization Toolkit for Transformers at Scale | mfuntowicz, echarlaix, michaelbenayoun, jeffboudier | hardware-partners-program.md | This post is the first step of a journey for Hugging Face to democratize
state-of-the-art **Machine Learning production performance**.
To get there, we will work hand in hand with our
Hardware Partners, as we have with Intel below.
Join us in this journey, and follow [Optimum](https://github.com/huggingface/optimum), o... | [
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a1f10e80-0036-4c2c-bf12-341194a8491a | completed | 2025-01-16T03:09:40.503651 | 2025-01-16T03:18:47.601400 | b2f071b2-2cbe-4c3a-bcd7-39bb8352d405 | Chat Templates: An End to the Silent Performance Killer | rocketknight1 | chat-templates.md | > *A spectre is haunting chat models - the spectre of incorrect formatting!*
## tl;dr
Chat models have been trained with very different formats for converting conversations into a single tokenizable string. Using a format different from the format a model was trained with will usually cause severe, silent performance... | [
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076efa0d-ec50-4a19-977e-787083074e41 | completed | 2025-01-16T03:09:40.503656 | 2025-01-16T03:15:25.503342 | 2c5dfa2c-3473-43c7-b2a4-2ab2ac79c488 | A Short Summary of Chinese AI Global Expansion | AdinaY | chinese-ai-expansion.md | In the early 15th century, Zheng He (also known as Chong Ho), a Chinese mariner and explorer during the early Ming Dynasty, led seven major naval expeditions, known as the "Voyages to the Western Oceans". His journey traced a path that went through Southeast Asia, the Middle East and then reached out to Africa. It was ... | [
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15de9078-a72f-432f-b36a-75baa7f54b2d | completed | 2025-01-16T03:09:40.503660 | 2025-01-19T17:06:30.151822 | 1651109e-6e00-428a-810d-bf5027c30e65 | A guide to setting up your own Hugging Face leaderboard: an end-to-end example with Vectara's hallucination leaderboard | ofermend, minseokbae, clefourrier | leaderboard-vectara.md | Hugging Face’s [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) (originally created by Ed Beeching and Lewis Tunstall, and maintained by Nathan Habib and Clémentine Fourrier) is well known for tracking the performance of open source LLMs, comparing their performance in a variety ... | [
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c92c17a2-6cd5-4bb7-8371-0849a89b8be5 | completed | 2025-01-16T03:09:40.503665 | 2025-01-16T03:24:43.451260 | 0bb56453-8391-416f-90a7-aae9920b8166 | Easily Train Models with H100 GPUs on NVIDIA DGX Cloud | philschmid, jeffboudier, rafaelpierrehf, abhishek | train-dgx-cloud.md | Today, we are thrilled to announce the launch of **Train on DGX Cloud**, a new service on the Hugging Face Hub, available to Enterprise Hub organizations. Train on DGX Cloud makes it easy to use open models with the accelerated compute infrastructure of NVIDIA DGX Cloud. Together, we built Train on DGX Cloud so that En... | [
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c2a865f5-ba92-4de6-9b4d-375a0f4f6ba1 | completed | 2025-01-16T03:09:40.503670 | 2025-01-16T03:19:57.208690 | 97667589-af8f-4eae-8f76-0a070ac287b4 | Deploy Livebook notebooks as apps to Hugging Face Spaces | josevalim | livebook-app-deployment.md | The [Elixir](https://elixir-lang.org/) community has been making great strides towards Machine Learning and Hugging Face is playing an important role on making it possible. To showcase what you can already achieve with Elixir and Machine Learning today, we use [Livebook](https://livebook.dev/) to build a Whisper-based ... | [
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7f09b5ad-2f0e-4c4e-b67a-94c5a8565937 | completed | 2025-01-16T03:09:40.503675 | 2025-01-19T17:18:46.222602 | 7429732b-3a9b-4450-b83f-cd7bd85bbe45 | Making ML-powered web games with Transformers.js | Xenova | ml-web-games.md | In this blog post, I'll show you how I made [**Doodle Dash**](https://huggingface.co/spaces/Xenova/doodle-dash), a real-time ML-powered web game that runs completely in your browser (thanks to [Transformers.js](https://github.com/xenova/transformers.js)). The goal of this tutorial is to show you how easy it is to make ... | [
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8586958a-7ca9-4de6-b099-4887ab26f4bf | completed | 2025-01-16T03:09:40.503679 | 2025-01-19T19:05:58.033311 | bf0f69ab-f484-49d1-bf47-b2ed6ba209f9 | Very Large Language Models and How to Evaluate Them | mathemakitten, Tristan, abhishek, lewtun, douwekiela | zero-shot-eval-on-the-hub.md | Large language models can now be evaluated on zero-shot classification tasks with [Evaluation on the Hub](https://huggingface.co/spaces/autoevaluate/model-evaluator)!
Zero-shot evaluation is a popular way for researchers to measure the performance of large language models, as they have been [shown](https://arxiv.org/... | [
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46d1724c-8e56-40d8-8af7-fdedd83352c7 | completed | 2025-01-16T03:09:40.503684 | 2025-01-16T13:34:25.944631 | a5f3f21b-6693-4c1a-b712-97a421fdc0e4 | Share your open ML datasets on Hugging Face Hub! | davanstrien, cfahlgren1, lhoestq, erinys | researcher-dataset-sharing.md | Hugging Face Hub makes it seamless to host and share datasets, trusted by many leading research institutions, companies, and government agencies, including [Nvidia](https://huggingface.co/nvidia), [Google](https://huggingface.co/google), [Stanford](https://huggingface.co/stanfordnlp), [NASA](https://huggingface.co/ibm-... | [
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1cf4ac3a-0332-4db5-8bd2-c8d38ff7b9fd | completed | 2025-01-16T03:09:40.503711 | 2025-01-19T19:04:21.979357 | 1c225821-ae52-4939-ba6c-9f5ea9d05be9 | Google Cloud TPUs made available to Hugging Face users | pagezyhf, michellehbn, philschmid, tengomucho | tpu-inference-endpoints-spaces.md | 
We're excited to share some great news! AI builders are now able to accelerate their applications with [Google Cloud TPUs](https://cloud.google.com/tpu?hl=en) on Hugging Face [Inference Endpoints](https... | [
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83b0be4d-302b-40d1-b7da-7ae204f70edd | completed | 2025-01-16T03:09:40.503719 | 2025-01-19T17:15:54.758621 | bce58cc3-4931-4105-ab96-cc2d541c1dc0 | Introducing Skops | merve, adrin, BenjaminB | skops.md | ## Introducing Skops
At Hugging Face, we are working on tackling various problems in open-source machine learning, including, hosting models securely and openly, enabling reproducibility, explainability and collaboration. We are thrilled to introduce you to our new library: Skops! With Skops, you can host your scikit-... | [
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5b107901-4d19-4b2f-8bb1-60a3693479a4 | completed | 2025-01-16T03:09:40.503727 | 2025-01-19T17:19:50.030779 | 687e6f2d-42fb-4c67-988c-1e29d3d48956 | Fine-Tune MMS Adapter Models for low-resource ASR | patrickvonplaten | mms_adapters.md | <a target="_blank" href="https://colab.research.google.com/github/patrickvonplaten/notebooks/blob/master/Fine_Tune_MMS_on_Common_Voice.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
***New (06/2023)***: *This blog post is strongly inspired by ["Fine-tuning XL... | [
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ed30aa58-b356-4cc9-8ca5-6ff2d879d3e3 | completed | 2025-01-16T03:09:40.503735 | 2025-01-16T03:11:00.395015 | 0672e2ab-9e0c-4a92-9d33-47d0da8bda72 | Introducing Storage Regions on the HF Hub | coyotte508, rtrm, XciD, michellehbn, violette, julien-c | regions.md | As part of our [Enterprise Hub](https://huggingface.co/enterprise) plan, we recently released support for **Storage Regions**.
Regions let you decide where your org's models and datasets will be stored. This has two main benefits, which we'll briefly go over in this blog post:
- **Regulatory and legal compliance**, an... | [
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afd5ce74-f3a2-455f-a583-461f1d926c98 | completed | 2025-01-16T03:09:40.503742 | 2025-01-19T18:53:33.766812 | f6c7e10d-df52-476d-b4b2-6383a069b7a9 | Finally, a Replacement for BERT: Introducing ModernBERT | bwarner, NohTow, bclavie, orionweller, ohallstrom, staghado, alexisgallagher, rbiswasfc, fladhak, tomaarsen, ncoop57, griffin, jph00, johnowhitaker, iacolippo | modernbert.md | ## TL;DR
This blog post introduces [ModernBERT](https://huggingface.co/collections/answerdotai/modernbert-67627ad707a4acbf33c41deb), a family of state-of-the-art encoder-only models representing improvements over older generation encoders across the board, with a **8192** sequence length, better downstream performance... | [
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bc1b7405-e8df-458b-a78f-c5849ef5c134 | completed | 2025-01-16T03:09:40.503747 | 2025-01-19T18:52:24.673803 | 2373e126-a7b8-4aa7-b7df-cbc48cd68326 | Accelerating Vision-Language Models: BridgeTower on Habana Gaudi2 | regisss, anahita-b | bridgetower.md | *Update (29/08/2023): A benchmark on H100 was added to this blog post. Also, all performance numbers have been updated with newer versions of software.*
[Optimum Habana v1.7](https://github.com/huggingface/optimum-habana/tree/main) on Habana Gaudi2 achieves **x2.5 speedups compared to A100 and x1.4 compared to H100** ... | [
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74d39494-88ce-4d6a-83c2-eb9e964bcac2 | completed | 2025-01-16T03:09:40.503752 | 2025-01-16T03:24:31.688615 | c2ce316c-6e23-4543-9d8f-17d4c3d84246 | Banque des Territoires (CDC Group) x Polyconseil x Hugging Face: Enhancing a Major French Environmental Program with a Sovereign Data Solution | AnthonyTruchet-Polyconseil, jcailton, StacyRamaherison, florentgbelidji, Violette | sovereign-data-solution-case-study.md | ## Table of contents
- Case Study in English - Banque des Territoires (CDC Group) x Polyconseil x Hugging Face: Enhancing a Major French Environmental Program with a Sovereign Data Solution
- [Executive summary](#executive-summary)
- [The power of RAG to meet environmental objectives](#power-of-rag)
- [... | [
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3545f879-8acb-4374-9066-61336746d30c | completed | 2025-01-16T03:09:40.503757 | 2025-01-16T03:24:47.738668 | 442d88f7-ee07-47ec-aeb0-e1b9cdd38e6a | Hyperparameter Search with Transformers and Ray Tune | ray-project | ray-tune.md | ##### A guest blog post by Richard Liaw from the Anyscale team
With cutting edge research implementations, thousands of trained models easily accessible, the Hugging Face [transformers](https://github.com/huggingface/transformers) library has become critical to the success and growth of natural language processing tod... | [
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42011b68-28ec-48c1-8952-36660110bd0f | completed | 2025-01-16T03:09:40.503761 | 2025-01-19T18:47:40.213637 | a0a9e351-5aee-4df1-adeb-ae430333eda7 | Efficient Table Pre-training without Real Data: An Introduction to TAPEX | SivilTaram | tapex.md | In recent years, language model pre-training has achieved great success via leveraging large-scale textual data. By employing pre-training tasks such as [masked language modeling](https://arxiv.org/abs/1810.04805), these models have demonstrated surprising performance on several downstream tasks. However, the dramatic ... | [
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ac677e6a-531d-453c-9e79-d314af9c88d8 | completed | 2025-01-16T03:09:40.503766 | 2025-01-16T03:22:06.491395 | a1a6a302-141e-49b9-8619-01fe6dc3cfe9 | Faster Text Generation with Self-Speculative Decoding | ariG23498, melhoushi, pcuenq, reach-vb | layerskip.md | Self-speculative decoding, proposed in
[LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding](https://arxiv.org/abs/2404.16710)
is a novel approach to text generation. It combines the strengths of speculative decoding with early
exiting from a large language model (LLM). This method allows for efficie... | [
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f923b084-6eaa-45f9-bb52-bc7393d21278 | completed | 2025-01-16T03:09:40.503770 | 2025-01-19T18:51:12.231023 | 0358447a-d16a-4ec4-8310-863578635b9a | Introducing SynthID Text | sumedhghaisas, sdathath, RyanMullins, joaogante, marcsun13, RaushanTurganbay | synthid-text.md | Do you find it difficult to tell if text was written by a human or generated by
AI? Being able to identify AI-generated content is essential to promoting trust
in information, and helping to address problems such as misattribution and
misinformation. Today, [Google DeepMind](https://deepmind.google/) and Hugging
Face a... | [
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40c05bd6-9807-4156-a25d-a0d6fe622640 | completed | 2025-01-16T03:09:40.503775 | 2025-01-19T17:13:13.165315 | 94a9cfe2-a1fb-49b6-9071-2342471df2e5 | Fine-Tune Wav2Vec2 for English ASR in Hugging Face with 🤗 Transformers | patrickvonplaten | fine-tune-wav2vec2-english.md | <a target="_blank" href="https://colab.research.google.com/github/patrickvonplaten/notebooks/blob/master/Fine_tuning_Wav2Vec2_for_English_ASR.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
Wav2Vec2 is a pretrained model for Automatic Speech Recognition (ASR)
... | [
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1fa271b0-71dd-4fb6-9c41-37de230b81f8 | completed | 2025-01-16T03:09:40.503780 | 2025-01-16T13:46:38.019933 | fe94205d-1bed-4d45-b72e-144b63865709 | 'Building a Playlist Generator with Sentence Transformers' | nimaboscarino | playlist-generator.md | <script async defer src="https://unpkg.com/medium-zoom-element@0/dist/medium-zoom-element.min.js"></script>
A short while ago I published a [playlist generator](https://huggingface.co/spaces/NimaBoscarino/playlist-generator) that I’d built using Sentence Transformers and Gradio, and I followed that up with a [reflecti... | [
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f39e1421-8299-4e73-b712-d5996bd02c1f | completed | 2025-01-16T03:09:40.503784 | 2025-01-16T03:16:00.128187 | 10c4d53e-be49-4fdd-8283-b0f6b21dd8f0 | How we sped up transformer inference 100x for 🤗 API customers | nan | accelerated-inference.md | 🤗 Transformers has become the default library for data scientists all around the world to explore state of the art NLP models and build new NLP features. With over 5,000 pre-trained and fine-tuned models available, in over 250 languages, it is a rich playground, easily accessible whichever framework you are working in... | [
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dd7cdd0f-0e19-4660-a805-9905b4fee190 | completed | 2025-01-16T03:09:40.503789 | 2025-01-19T19:05:06.966736 | 7da7ebbd-0ba3-4a0d-9732-51e6d4fea84b | Ethics and Society Newsletter #3: Ethical Openness at Hugging Face | irenesolaiman, giadap, NimaBoscarino, yjernite, allendorf, meg, sasha | ethics-soc-3.md | ## Mission: Open and Good ML
In our mission to democratize good machine learning (ML), we examine how supporting ML community work also empowers examining and preventing possible harms. Open development and science decentralizes power so that many people can collectively work on AI that reflects their needs and values.... | [
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2b500d83-9eee-40db-9f25-17064aa2f7e7 | completed | 2025-01-16T03:09:40.503793 | 2025-01-16T13:37:09.893346 | 5a68dae1-c6eb-4658-af2d-bc1dfc692797 | Fine-tune Llama 2 with DPO | kashif, ybelkada, lvwerra | dpo-trl.md | ## Introduction
Reinforcement Learning from Human Feedback (RLHF) has become the de facto last training step of LLMs such as GPT-4 or Claude to ensure that the language model's outputs are aligned with human expectations such as chattiness or safety features. However, it brings some of the complexity of RL into NLP: w... | [
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c806de3c-9caf-451c-afc3-b939b9657245 | completed | 2025-01-16T03:09:40.503798 | 2025-01-19T18:50:40.976128 | f6615834-a4f1-4000-b64c-e044e3f1ec21 | Deep Learning with Proteins | rocketknight1 | deep-learning-with-proteins.md | I have two audiences in mind while writing this. One is biologists who are trying to get into machine learning, and the other is machine learners who are trying to get into biology. If you’re not familiar with either biology or machine learning then you’re still welcome to come along, but you might find it a bit confus... | [
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feea7686-2a87-47de-bd75-7e5d2c415e63 | completed | 2025-01-16T03:09:40.503802 | 2025-01-16T03:23:39.848944 | 56c95c7f-545b-45b7-831f-aacfb90c394b | Announcing the Open Source AI Game Jam 🎮 | ThomasSimonini | game-jam.md | <h2> Unleash Your Creativity with AI Tools and make a game in a weekend!</h2>
<!-- {authors} -->
We're thrilled to announce the first ever **Open Source AI Game Jam**, where you will create a game using AI tools.
With AI's potential to enhance game experiences and workflows, we're excited to see what you can accomp... | [
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ed430ab5-f68f-4ca0-8652-6ef1a7741e43 | completed | 2025-01-16T03:09:40.503807 | 2025-01-19T18:48:02.566981 | 2ad9c451-7d68-4db5-a791-b3416ab282b4 | Deploy GPT-J 6B for inference using Hugging Face Transformers and Amazon SageMaker | philschmid | gptj-sagemaker.md | <script async defer src="https://unpkg.com/medium-zoom-element@0/dist/medium-zoom-element.min.js"></script>
Almost 6 months ago to the day, [EleutherAI](https://www.eleuther.ai/) released [GPT-J 6B](https://huggingface.co/EleutherAI/gpt-j-6B), an open-source alternative to [OpenAIs GPT-3](https://openai.com/blog/gpt-... | [
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2012cca4-f430-44a7-a151-bb534bf477c9 | completed | 2025-01-16T03:09:40.503812 | 2025-01-19T19:02:48.517297 | 6b582e06-c7fa-4079-8b9c-4301696a0903 | Introducing HUGS - Scale your AI with Open Models | philschmid, jeffboudier, alvarobartt, pagezyhf, Violette | hugs.md | 
## Zero-Configuration Optimized Inference for Open Models
HUGS simplifies the optimized deployment of open models in your own infrastructure and on a wide variety of hardware. One key challenge develope... | [
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d58f9d56-8693-40a2-ba69-c4582f577b0e | completed | 2025-01-16T03:09:40.503816 | 2025-01-19T18:53:12.718314 | 0385fdcf-f0bd-4f9d-b5dc-e9d2ee0a0cac | From cloud to developers: Hugging Face and Microsoft Deepen Collaboration | jeffboudier, philschmid | microsoft-collaboration.md | Today at Microsoft Build we are happy to announce a broad set of new features and collaborations as Microsoft and Hugging Face deepen their strategic collaboration to make open models and open source AI easier to use everywhere. Together, we will work to enable AI builders across open science, open source, cloud, hardw... | [
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a239163b-0c83-49ba-8903-d54690b172d6 | completed | 2025-01-16T03:09:40.503821 | 2025-01-16T03:23:06.897872 | 0bac6ee0-8fee-44eb-9bb3-4f25c0956e1e | Subscribe to Enterprise Hub with your AWS Account | Violette, sbrandeis, jeffboudier | enterprise-hub-aws-marketplace.md | You can now upgrade your Hugging Face Organization to Enterprise using your AWS account - get started [on the AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-n6vsyhdjkfng2).
## What is Enterprise Hub?
[Enterprise Hub](https://huggingface.co/enterprise) is a premium subscription to upgrade a free Hugg... | [
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69353503-2c29-4e20-8f51-760900e73371 | completed | 2025-01-16T03:09:40.503826 | 2025-01-18T14:44:25.691317 | 461ed2a8-9f85-4011-85be-b1c7b1f25ce9 | Graphcore and Hugging Face Launch New Lineup of IPU-Ready Transformers | sallydoherty | graphcore-update.md | [Graphcore](https://huggingface.co/hardware/graphcore/) and Hugging Face have significantly expanded the range of Machine Learning modalities and tasks available in [Hugging Face Optimum](https://github.com/huggingface/optimum), an open-source library for Transformers performance optimization. Developers now have conve... | [
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2a6e3f27-b13d-4f22-9523-287c75c771c9 | completed | 2025-01-16T03:09:40.503830 | 2025-01-16T03:19:37.175860 | 0d86df47-797f-4d1b-a920-0661b8950c28 | Welcome, Gradio 5 | abidlabs | gradio-5.md | We’ve been hard at work over the past few months, and we are excited to now announce the **stable release of Gradio 5**.
With Gradio 5, developers can build **production-ready machine learning web applications** that are performant, scalable, beautifully designed, accessible, and follow best web security practices, a... | [
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88cdecec-e682-40e1-8b23-3d61aeff53f0 | completed | 2025-01-16T03:09:40.503835 | 2025-01-16T03:15:30.764547 | fb216ef4-d053-41b7-9682-079adfe0c54e | Introducing the Enterprise Scenarios Leaderboard: a Leaderboard for Real World Use Cases | sunitha98, RebeccaQian, anandnk24, clefourrier | leaderboard-patronus.md | Today, the Patronus team is excited to announce the new [Enterprise Scenarios Leaderboard](https://huggingface.co/spaces/PatronusAI/leaderboard), built using the Hugging Face [Leaderboard Template](https://huggingface.co/demo-leaderboard-backend) in collaboration with their teams.
The leaderboard aims to evaluate the... | [
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221e494c-2c1d-4d45-bf5f-9bbf6f03bc10 | completed | 2025-01-16T03:09:40.503840 | 2025-01-16T03:23:16.592374 | 96c82c2c-d591-4718-b780-b13f2bb9ec71 | Scaling robotics datasets with video encoding | aliberts, cadene, mfarre | video-encoding.md | Over the past few years, text and image-based models have seen dramatic performance improvements, primarily due to scaling up model weights and dataset sizes. While the internet provides an extensive database of text and images for LLMs and image generation models, robotics lacks such a vast and diverse qualitative dat... | [
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d537891d-4e19-4576-abb9-fb3ff6f1f2f6 | completed | 2025-01-16T03:09:40.503844 | 2025-01-19T18:55:42.272654 | 9bc89a3d-8d25-41a5-ae30-b519d7b2a07c | Total noob’s intro to Hugging Face Transformers | 2legit2overfit | noob_intro_transformers.md | Welcome to "A Total Noob’s Introduction to Hugging Face Transformers," a guide designed specifically for those looking to understand the bare basics of using open-source ML. Our goal is to demystify what Hugging Face Transformers is and how it works, not to turn you into a machine learning practitioner, but to enable b... | [
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126711e9-657e-4667-a2db-4a46578aa60e | completed | 2025-01-16T03:09:40.503849 | 2025-01-19T18:49:50.883206 | 42cf7b71-5f42-44e0-86c9-657253906181 | Diffusers welcomes Stable Diffusion 3 | dn6, YiYiXu, sayakpaul, OzzyGT, kashif, multimodalart | sd3.md | [Stable Diffusion 3](https://stability.ai/news/stable-diffusion-3-research-paper) (SD3), Stability AI’s latest iteration of the Stable Diffusion family of models, is now available on the Hugging Face Hub and can be used with 🧨 Diffusers.
The model released today is Stable Diffusion 3 Medium, with 2B parameters.
As p... | [
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97c54919-858d-4132-bf54-8c6ff234bd6b | completed | 2025-01-16T03:09:40.503854 | 2025-01-16T13:32:49.560345 | afe31015-d251-4a0e-a3f2-90b812062d76 | Sentiment Analysis on Encrypted Data with Homomorphic Encryption | jfrery-zama | sentiment-analysis-fhe.md | It is well-known that a sentiment analysis model determines whether a text is positive, negative, or neutral. However, this process typically requires access to unencrypted text, which can pose privacy concerns.
Homomorphic encryption is a type of encryption that allows for computation on encrypted data without needin... | [
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070992d7-d909-4efb-b64d-140b363294c1 | completed | 2025-01-16T03:09:40.503858 | 2025-01-16T15:13:42.644388 | 41d7f6c2-224a-4ecc-b1a9-600e9482ec5d | Run a Chatgpt-like Chatbot on a Single GPU with ROCm | andyll7772 | chatbot-amd-gpu.md | ## Introduction
ChatGPT, OpenAI's groundbreaking language model, has become an
influential force in the realm of artificial intelligence, paving the
way for a multitude of AI applications across diverse sectors. With its
staggering ability to comprehend and generate human-like text, ChatGPT
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b963df34-6cea-4623-9fc1-415700562001 | completed | 2025-01-16T03:09:40.503863 | 2025-01-19T19:05:40.246697 | 5b5e4352-1871-44ae-a741-ce93bcfee479 | TGI Multi-LoRA: Deploy Once, Serve 30 Models | derek-thomas, dmaniloff, drbh | multi-lora-serving.md | Are you tired of the complexity and expense of managing multiple AI models? **What if you could deploy once and serve 30 models?** In today's ML world, organizations looking to leverage the value of their data will likely end up in a _fine-tuned world_, building a multitude of models, each one highly specialized for a ... | [
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076530d2-0653-4e7a-b5bb-ee7289303a2b | completed | 2025-01-16T03:09:40.503868 | 2025-01-19T17:15:18.240007 | a61c394e-2526-4a52-a535-0763e6eb577a | Perceiver IO: a scalable, fully-attentional model that works on any modality | nielsr | perceiver.md | ### TLDR
We've added [Perceiver IO](https://huggingface.co/docs/transformers/model_doc/perceiver) to Transformers, the first Transformer-based neural network that works on all kinds of modalities (text, images, audio, video, point clouds,...) and combinations thereof. Take a look at the following Spaces to view some e... | [
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d71c96e3-7b8d-4c45-bd26-f3d3a0d375a8 | completed | 2025-01-16T03:09:40.503872 | 2025-01-16T13:37:16.038411 | 5290f5db-71e3-4634-85e9-7e2fecb2b693 | Faster Stable Diffusion with Core ML on iPhone, iPad, and Mac | pcuenq | fast-diffusers-coreml.md | WWDC’23 (Apple Worldwide Developers Conference) was held last week. A lot of the news focused on the Vision Pro announcement during the keynote, but there’s much more to it. Like every year, WWDC week is packed with more than 200 technical sessions that dive deep inside the upcoming features across Apple operating syst... | [
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dcfdeb3a-0697-40d1-bc93-e4e061160b40 | completed | 2025-01-16T03:09:40.503877 | 2025-01-16T03:14:32.942938 | eae55332-626d-457b-aa6c-56b100ce8549 | Introducing DOI: the Digital Object Identifier to Datasets and Models | sasha, Sylvestre, christopher, aleroy | introducing-doi.md | Our mission at Hugging Face is to democratize good machine learning. That includes best practices that make ML models and datasets more reproducible, better documented, and easier to use and share.
To solve this challenge, **we're excited to announce that you can now generate a DOI for your model or dataset directly f... | [
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f59dfdbf-9a32-416c-863e-36310ce967fa | completed | 2025-01-16T03:09:40.503881 | 2025-01-19T19:13:11.791915 | 8fe20415-4561-46f6-b8ff-1d736710e117 | Space secrets security update | huggingface | space-secrets-disclosure.md | Earlier this week our team detected unauthorized access to our Spaces platform, specifically related to Spaces secrets. As a consequence, we have suspicions that a subset of Spaces’ secrets could have been accessed without authorization.
As a first step of remediation, we have revoked a number of HF tokens present in ... | [
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b47b4920-ee41-48eb-a8ad-82f7bb6b1928 | completed | 2025-01-16T03:09:40.503886 | 2025-01-19T17:17:28.490938 | e6cd4a79-c361-44ca-9ab9-77e8140dfb59 | GaLore: Advancing Large Model Training on Consumer-grade Hardware | Titus-von-Koeller, jiaweizhao, mdouglas, hiyouga, ybelkada, muellerzr, amyeroberts, smangrul, BenjaminB | galore.md | The integration of GaLore into the training of large language models (LLMs) marks a significant advancement in the field of deep learning, particularly in terms of memory efficiency and the democratization of AI research. By allowing for the training of billion-parameter models on consumer-grade hardware, reducing memo... | [
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fcc67b53-66f8-4acb-adf4-009558dae823 | completed | 2025-01-16T03:09:40.503890 | 2025-01-19T17:16:11.027003 | 8ec0ae1b-1dbb-4a4e-82e0-0b0f2154c6aa | The N Implementation Details of RLHF with PPO | vwxyzjn, tianlinliu0121, lvwerra | the_n_implementation_details_of_rlhf_with_ppo.md | RLHF / ChatGPT has been a popular research topic these days. In our quest to research more on RLHF, this blog post attempts to do a reproduction of OpenAI’s 2019 original RLHF codebase at [*openai/lm-human-preferences*](https://github.com/openai/lm-human-preferences). Despite its “tensorflow-1.x-ness,” OpenAI’s origina... | [
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fe646e6c-2a2c-4d52-a4a6-058fed31034c | completed | 2025-01-16T03:09:40.503895 | 2025-01-16T03:25:38.934718 | 821564d2-ac1a-4ddd-a7db-398069840d58 | Introducing the Chatbot Guardrails Arena | sonalipnaik, rohankaran, srijankedia, clefourrier | arena-lighthouz.md | With the recent advancements in augmented LLM capabilities, deployment of enterprise AI assistants (such as chatbots and agents) with access to internal databases is likely to increase; this trend could help with many tasks, from internal document summarization to personalized customer and employee support. However, da... | [
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114ef39e-d868-4afe-8fad-ffcce11672ba | completed | 2025-01-16T03:09:40.503899 | 2025-01-19T19:15:52.146229 | 1d998513-9a5c-4ad2-892c-17ddbe89499d | Optimization story: Bloom inference | Narsil | bloom-inference-optimization.md | This article gives you the behind-the-scenes of how we made an efficient inference server that powers bloom.
inference server that powers [https://huggingface.co/bigscience/bloom]().
We achieved a 5x latency reduction over several weeks (and 50x more throughput). We wanted to share all the struggles and epic wins we w... | [
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c7261fd2-02af-43d1-80b1-435585236b6a | completed | 2025-01-16T03:09:40.503904 | 2025-01-16T14:20:49.961018 | 904ec765-fa9f-4392-bd3f-df741ced4302 | Accelerate your models with 🤗 Optimum Intel and OpenVINO | echarlaix, juliensimon | openvino.md | 
Last July, we [announced](https://huggingface.co/blog/intel) that Intel and Hugging Face would collaborate on building state-of-the-art yet simple hardware acceleration tools for Transformer models.
Today, we are very happy to announce that we added Intel [OpenVINO](https... | [
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88450e72-79a2-45c1-95ad-d7ab2a532c1a | completed | 2025-01-16T03:09:40.503910 | 2025-01-19T18:55:38.759878 | 77c0e873-0d7d-4583-85c9-638eda937751 | Comments on U.S. National AI Research Resource Interim Report | irenesolaiman | us-national-ai-research-resource.md | In late June 2022, Hugging Face submitted a response to the White House Office of Science and Technology Policy and National Science Foundation’s Request for Information on a roadmap for implementing the National Artificial Intelligence Research Resource (NAIRR) Task Force’s interim report findings. As a platform worki... | [
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d1dcf295-bfea-448c-b39a-eee36ac4bc2b | completed | 2025-01-16T03:09:40.503915 | 2025-01-16T13:32:54.276807 | fb8a716b-966d-40e9-a8c4-af6f19b7345a | Hugging Face Collaborates with Microsoft to launch Hugging Face Model Catalog on Azure | jeffboudier, philschmid, juliensimon | hugging-face-endpoints-on-azure.md | 
Today, we are thrilled to announce that Hugging Face expands its collaboration with Microsoft to bring open-source models from the Hugging Face Hub to Azure Machine Learning. Together we built a new H... | [
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fcad8c31-a111-44d2-b374-c584d2c7d4de | completed | 2025-01-16T03:09:40.503920 | 2025-01-19T19:12:53.775627 | 3e0f6152-25ec-4f14-ad7c-504087f0ea03 | Faster Assisted Generation with Dynamic Speculation | jmamou, orenpereg, joaogante, lewtun, danielkorat, Nadav-Timor, moshew | dynamic_speculation_lookahead.md | ## Speculative Decoding
[Speculative decoding](https://arxiv.org/abs/2211.17192) is a popular technique to accelerate the inference of large language models, while preserving their accuracy. As shown in the figure below, speculative decoding works by splitting the generative process into two stages. In the first stage,... | [
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b9fd56ec-0324-4268-9ee1-74be72a1a5f6 | completed | 2025-01-16T03:09:40.503925 | 2025-01-19T18:51:35.198982 | b0b13777-9085-4938-a663-de47229667a6 | Introducing HuggingFace blog for Chinese speakers: Fostering Collaboration with the Chinese AI community | xianbao, adinayakefu, chenglu | chinese-language-blog.md | ## Welcome to our blog for Chinese speakers!
We are delighted to introduce Hugging Face’s new blog for Chinese speakers: [hf.co/blog/zh](https://huggingface.co/blog/zh)! A committed group of volunteers has made this possible by translating our invaluable resources, including blog posts and comprehensive courses on tra... | [
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278fdb57-6d58-4d48-a512-b397edaec049 | completed | 2025-01-16T03:09:40.503929 | 2025-01-19T19:06:07.552244 | 360c3cd9-9745-4a58-9550-0ceb34ca4292 | Inference for PROs | osanseviero, pcuenq, victor | inference-pro.md | 
Today, we're introducing Inference for PRO users - a community offering that gives you access to APIs of curated endpoints for some of the most exciting models avail... | [
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6e5884d6-0304-4c4b-9e66-3c442ac721e0 | completed | 2025-01-16T03:09:40.503934 | 2025-01-16T03:21:25.037473 | ee2dd9be-8acf-4858-87d9-cc63279002a0 | Ethical Guidelines for developing the Diffusers library | giadap | ethics-diffusers.md | We are on a journey to make our libraries more responsible, one commit at a time!
As part of the [Diffusers library documentation](https://huggingface.co/docs/diffusers/main/en/index), we are proud to announce the publication of an [ethical framework](https://huggingface.co/docs/diffusers/main/en/conceptual/ethical_g... | [
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72dedd0f-7007-4eea-8c88-ed04a2fb49e1 | completed | 2025-01-16T03:09:40.503939 | 2025-01-19T19:06:36.862053 | b637edc1-2940-4ad1-96d7-f9fccfba7dec | Visualize proteins on Hugging Face Spaces | simonduerr | spaces_3dmoljs.md | In this post we will look at how we can visualize proteins on Hugging Face Spaces.
**Update May 2024**
While the method described below still works, you'll likely want to save some time and use the [Molecule3D Gradio Custom Component](https://www.gradio.app/custom-components/gallery?id=simonduerr%2Fgradio_molecule3d)... | [
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803309b2-517f-4bdd-8865-782901735be3 | completed | 2025-01-16T03:09:40.503944 | 2025-01-16T15:15:58.742672 | 28db7934-140b-4f12-b246-0528d16c9fb0 | Announcing New Dataset Search Features | lhoestq, severo, kramp | datasets-filters.md | The AI and ML community has shared more than 180,000 public datasets on The [Hugging Face Dataset Hub](https://huggingface.co/datasets).
Researchers and engineers are using these datasets for various tasks, from training LLMs to chat with users to evaluating automatic speech recognition or computer vision systems.
Data... | [
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b2da00f4-0bf7-4e6d-af56-ab0138a4f7da | completed | 2025-01-16T03:09:40.503948 | 2025-01-19T18:47:32.592926 | b0c8f57a-515f-4c11-86f3-4595300779af | Illustrating Reinforcement Learning from Human Feedback (RLHF) | natolambert, LouisCastricato, lvwerra, Dahoas | rlhf.md | _This article has been translated to Chinese [简体中文](https://huggingface.co/blog/zh/rlhf) and Vietnamese [đọc tiếng việt](https://trituenhantao.io/kien-thuc/minh-hoa-rlhf-vu-khi-dang-sau-gpt/)_.
Language models have shown impressive capabilities in the past few years by generating diverse and compelling text from huma... | [
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1e1bc4a9-8ab1-4218-b9ca-f6a03b6568d2 | completed | 2025-01-16T03:09:40.503953 | 2025-01-16T13:38:51.325154 | 85a25f2f-9d2b-44ac-9032-809cb66f5f7c | AI Watermarking 101: Tools and Techniques | sasha, yjernite, derek-thomas, EmilyWitko, Ezi, JJoe206, reach-vb, BrigitteTousi, meg | watermarking.md | In recent months, we've seen multiple news stories involving ‘deepfakes’, or AI-generated content: from [images of Taylor Swift](https://www.npr.org/2024/01/26/1227091070/deepfakes-taylor-swift-images-regulation) to [videos of Tom Hanks](https://www.theguardian.com/film/2023/oct/02/tom-hanks-dental-ad-ai-version-fake) ... | [
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c977037a-5c07-4818-b022-60e17b1c14b4 | completed | 2025-01-16T03:09:40.503958 | 2025-01-19T17:16:38.788208 | bc71802a-0cd3-4155-be40-083bc18522ad | Putting ethical principles at the core of the research lifecycle | SaulLu, skaramcheti, HugoLaurencon, Leyo, TimeRobber, VictorSanh, aps, giadap, sasha, yjernite, meg, douwekiela | ethical-charter-multimodal.md | ## Ethical charter - Multimodal project
## Purpose of the ethical charter
It has been well documented that machine learning research and applications can potentially lead to "data privacy issues, algorithmic biases, automation risks and malicious uses" (NeurIPS 2021 [ethics guidelines](https://nips.cc/public/EthicsG... | [
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261d8d5a-02c3-4eee-8a7a-bf139ee6eba4 | completed | 2025-01-16T03:09:40.503963 | 2025-01-16T03:18:56.938128 | a8c7964e-8e26-45fa-b942-693346c63ab7 | AI Policy @🤗: Open ML Considerations in the EU AI Act | yjernite | eu-ai-act-oss.md | Like everyone else in Machine Learning, we’ve been following the EU AI Act closely at Hugging Face.
It’s a ground-breaking piece of legislation that is poised to shape how democratic inputs interact with AI technology development around the world.
It’s also the outcome of extensive work and negotiations between organiz... | [
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bd14cdd1-d1ed-407d-b79e-20cd9c8b0cba | completed | 2025-01-16T03:09:40.503967 | 2025-01-19T18:47:51.584678 | 03674f00-5d20-460c-b75f-927723c7bb73 | Model Cards | Ezi, Marissa, Meg | model-cards.md | ## Introduction
Model cards are an important documentation framework for understanding, sharing, and improving machine learning models. When done well, a model card can serve as a _boundary object_, a single artefact that is accessible to people with different backgrounds and goals in understanding models - including d... | [
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09dd2855-8ca6-4b98-b2b7-3446454217fa | completed | 2025-01-16T03:09:40.503972 | 2025-01-16T13:36:55.299910 | c86022f4-401f-40a5-a81f-f49fd36b257a | How to host a Unity game in a Space | dylanebert | unity-in-spaces.md | <!-- {authors} -->
Did you know you can host a Unity game in a Hugging Face Space? No? Well, you can!
Hugging Face Spaces are an easy way to build, host, and share demos. While they are typically used for Machine Learning demos,
they can also host playable Unity games. Here are some examples:
- [Huggy](https://hug... | [
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ffcfd24c-d738-43d4-a9d2-b893b6ef2933 | completed | 2025-01-16T03:09:40.503977 | 2025-01-16T14:19:55.066492 | 57474393-216e-44fd-9a70-370cc8fbeb0a | 2023, year of open LLMs | clefourrier | 2023-in-llms.md | 2023 has seen a surge of public interest in Large Language Models (LLMs), and now that most people have an idea of what they are and can do, the public debates around open versus closed source have reached a wide audience as well. At Hugging Face, we follow open models with great interest, as they allow research to be ... | [
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fd0bc08a-d587-4232-a148-5882e453040c | completed | 2025-01-16T03:09:40.503981 | 2025-01-19T18:49:09.071368 | c3c9f8be-fbb7-4142-847f-fc51edcfde6a | The Hallucinations Leaderboard, an Open Effort to Measure Hallucinations in Large Language Models | pminervini, pingnieuk, clefourrier, rohitsaxena, aryopg, zodiache | leaderboard-hallucinations.md | In the rapidly evolving field of Natural Language Processing (NLP), Large Language Models (LLMs) have become central to AI's ability to understand and generate human language. However, a significant challenge that persists is their tendency to hallucinate — i.e., producing content that may not align with real-world fac... | [
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7893763a-e118-4787-8349-e0e5d401ad3b | completed | 2025-01-16T03:09:40.503986 | 2025-01-19T19:04:02.109817 | 1d28ac50-41e4-4b1a-9d6b-94be896d2874 | VQ-Diffusion | williamberman | vq-diffusion.md | Vector Quantized Diffusion (VQ-Diffusion) is a conditional latent diffusion model developed by the University of Science and Technology of China and Microsoft. Unlike most commonly studied diffusion models, VQ-Diffusion's noising and denoising processes operate on a quantized latent space, i.e., the latent space is com... | [
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1321cf5c-cb4c-4abc-a650-9774f85385e7 | completed | 2025-01-16T03:09:40.503990 | 2025-01-19T18:55:31.749867 | 26952996-a2f9-432d-a40c-45efbff37114 | Fine-tuning Florence-2 - Microsoft's Cutting-edge Vision Language Models | andito, merve, SkalskiP | finetune-florence2.md | Florence-2, released by Microsoft in June 2024, is a foundation vision-language model. This model is very attractive because of its small size (0.2B and 0.7B) and strong performance on a variety of computer vision and vision-language tasks.
Florence supports many tasks out of the box: captioning, object detection, OCR... | [
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9ebaf163-f6ec-4b38-b1e6-a12ec8a169e7 | completed | 2025-01-16T03:09:40.503995 | 2025-01-19T19:12:13.982905 | 997ca2b8-219b-440f-bd4b-ca5aa7cefd62 | Blazing Fast SetFit Inference with 🤗 Optimum Intel on Xeon | danielkorat, tomaarsen, orenpereg, moshew, echarlaix, aprabh2 | setfit-optimum-intel.md | SetFit is a promising solution for a common modeling problem: how to deal with lack of labeled data for training. Developed with Hugging Face’s research partners at [Intel Labs](https://www.intel.com/content/www/us/en/research/overview.html) and the [UKP Lab](https://www.informatik.tu-darmstadt.de/ukp/ukp_home/index.en... | [
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93184a18-13e3-417f-ba22-25f6f799267f | completed | 2025-01-16T03:09:40.503999 | 2025-01-19T18:47:59.063537 | 2348a313-f518-4b94-932d-2d33df829303 | Fit More and Train Faster With ZeRO via DeepSpeed and FairScale | stas | zero-deepspeed-fairscale.md | **A guest blog post by Hugging Face fellow Stas Bekman**
As recent Machine Learning models have been growing much faster than the amount of GPU memory added to newly released cards, many users are unable to train or even just load some of those huge models onto their hardware. While there is an ongoing effort to dis... | [
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7f004f37-a4a6-441d-9201-924ccdc20d8c | completed | 2025-01-16T03:09:40.504004 | 2025-01-16T14:20:08.354473 | f76fb23c-bba5-4da1-a657-c5e7283f2041 | Patch Time Series Transformer in Hugging Face | namctin, wmgifford, ajati, vijaye12, kashif | patchtst.md | <script async defer src="https://unpkg.com/medium-zoom-element@0/dist/medium-zoom-element.min.js"></script>
<a target="_blank" href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/patch_tst.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In C... | [
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ea23d673-2acb-45f2-88f6-af683ec7c961 | completed | 2025-01-16T03:09:40.504008 | 2025-01-16T03:16:48.598263 | 8db66696-aecb-4424-8693-ed10870bfd1c | Case Study: Millisecond Latency using Hugging Face Infinity and modern CPUs | philschmid, jeffboudier, mfuntowicz | infinity-cpu-performance.md | <script async defer src="https://unpkg.com/medium-zoom-element@0/dist/medium-zoom-element.min.js"></script>
<br>
<div style="background-color: #e6f9e6; padding: 16px 32px; outline: 2px solid; border-radius: 10px;">
December 2022 Update: Infinity is no longer offered by Hugging Face as a commercial inference solution... | [
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aed1abdf-bacd-48b6-92c1-e57d834dde6e | completed | 2025-01-16T03:09:40.504013 | 2025-01-16T13:39:22.629736 | e747067c-c79c-4d6e-9be6-32dccb946e06 | A Dive into Text-to-Video Models | adirik | text-to-video.md | <p align="center">
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/140_text-to-video/text-to-video-samples.gif" alt="video-samples"><br>
<em>Video samples generated with <a href=https://modelscope.cn/models/damo/text-to-video-synthesis/summary>ModelScope</a>.</em>
</... | [
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98017a4e-2cf6-4a65-960c-5a079f84acae | completed | 2025-01-16T03:09:40.504017 | 2025-01-16T03:23:48.040145 | 18fc42d6-5ea1-4968-b739-77e2148aa058 | Policy Gradient with PyTorch | ThomasSimonini | deep-rl-pg.md | <h2>Unit 5, of the <a href="https://github.com/huggingface/deep-rl-class">Deep Reinforcement Learning Class with Hugging Face 🤗</a></h2>
⚠️ A **new updated version of this article is available here** 👉 [https://huggingface.co/deep-rl-course/unit1/introduction](https://huggingface.co/deep-rl-course/unit4/introduct... | [
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35189e6e-1180-4bed-9e67-0f59b00f1ec4 | completed | 2025-01-16T03:09:40.504022 | 2025-01-19T17:15:29.711351 | b698a25f-2f19-4fb9-abee-dbe1fc72e861 | Accelerating Hugging Face Transformers with AWS Inferentia2 | philschmid, juliensimon | accelerate-transformers-with-inferentia2.md | <script async defer src="https://unpkg.com/medium-zoom-element@0/dist/medium-zoom-element.min.js"></script>
In the last five years, Transformer models [[1](https://arxiv.org/abs/1706.03762)] have become the _de facto_ standard for many machine learning (ML) tasks, such as natural language processing (NLP), computer vi... | [
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