Kimi K3 Model Overview: 2.8T Parameters, MXFP4 Quantization, and What the Open Weights Mean for the Community
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guide
Hosting your Models and Datasets on Hugging Face Spaces using Streamlit
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October 5, 2021 
guide
Showcase Your Projects in Spaces using Gradio
14
October 5, 2021 
community
Summer at Hugging Face
September 24, 2021
graphcorepartnerships
Hugging Face and Graphcore partner for IPU-optimized Transformers
2
September 14, 2021 
guide
Introducing Optimum: The Optimization Toolkit for Transformers at Scale
2
September 14, 2021 
research
Deep Learning over the Internet: Training Language Models Collaboratively
7
July 15, 2021 
open-source-collabnlp
Welcome spaCy to the Hugging Face Hub
1
July 13, 2021 
guidepartnershipsaws
Deploy Hugging Face models easily with Amazon SageMaker
2
July 8, 2021 
open-source-collabnlp
Sentence Transformers in the Hugging Face Hub
June 28, 2021
guidenlp
Few-shot learning in practice: GPT-Neo and the 🤗 Accelerated Inference API
9
June 3, 2021 
open-source-collabguide
Using & Mixing Hugging Face Models with Gradio 2.0
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May 25, 2021 
guidenlppartnerships
Scaling-up BERT Inference on CPU (Part 1)
5
April 20, 2021 
guide
Introducing 🤗 Accelerate
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April 16, 2021 
guidepartnershipsaws
Distributed Training: Train BART/T5 for Summarization using 🤗 Transformers and Amazon SageMaker
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April 8, 2021 NEW Articles from Team or Enterprise organizations will get promoted to the main section.
Kimi K3 Model Overview: 2.8T Parameters, MXFP4 Quantization, and What the Open Weights Mean for the Community
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