Instructions to use hung200504/cpgqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hung200504/cpgqa with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="hung200504/cpgqa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hung200504/cpgqa") model = AutoModelForQuestionAnswering.from_pretrained("hung200504/cpgqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hung200504/cpgqa: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/hung200504/cpgqa/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hung200504/cpgqa/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hung200504/cpgqa/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- c098769abd940469e696156069076c1190e6e9e4e1d87be4c1e98f347a016b58
- Size of remote file:
- 431 MB
- SHA256:
- d3e32056afeb510c0c6bdb2a854388fc6a805e986c097739ddb31108c2579fc7
路
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