Instructions to use Ansh989/Chatbot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ansh989/Chatbot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Ansh989/Chatbot")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Ansh989/Chatbot", dtype="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: apache-2.0
datasets:
- WillHeld/india_accent_cv
- fka/awesome-chatgpt-prompts
- open-thoughts/OpenThoughts-114k
- open-r1/OpenR1-Math-220k
- BAAI/IndustryCorpus2_tourism_geography
- chungimungi/Indian-History
- nguha/legalbench
- PrimeIntellect/verifiable-coding-problems
- ajibawa-2023/Education-High-School-Students
- Gryphe/ChatGPT-4o-Writing-Prompts
- Congliu/Chinese-DeepSeek-R1-Distill-data-110k
- cfilt/iitb-english-hindi
- suayptalha/Poetry-Foundation-Poems
- BashitAli/Indian_history
- lmms-lab/ScienceQA
- Heuehneje/contitution-of-bhutan
- taesiri/GameplayCaptions-Gemini-pro-vision
- angie-chen55/javascript-github-code
language:
- en
- hi
- bn
- ja
- ko
metrics:
- accuracy
base_model:
- openai-community/gpt2
pipeline_tag: question-answering
library_name: transformers
tags:
- Chatbot
- text-generation-inference
- Question answering