Instructions to use catpawdev/QA_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use catpawdev/QA_model 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="catpawdev/QA_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("catpawdev/QA_model") model = AutoModelForQuestionAnswering.from_pretrained("catpawdev/QA_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from catpawdev/QA_model: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/catpawdev/QA_model/resolve/main/training_args.bin
- Command line
-
hf download hf://catpawdev/QA_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/catpawdev/QA_model/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- d372a7456a7e6fea5bb936d1a29fcee51417c51bf5fcc841206557cb952a93a3
- Size of remote file:
- 4.54 kB
- SHA256:
- 176bd2b47651c36cd8ecbcc94444b75fe3434596c0ccf2f93f6bcd25901c1f23
路
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