Instructions to use idah4/my_first_qa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use idah4/my_first_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="idah4/my_first_qa_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("idah4/my_first_qa_model") model = AutoModelForQuestionAnswering.from_pretrained("idah4/my_first_qa_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from idah4/my_first_qa_model: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/idah4/my_first_qa_model/resolve/main/training_args.bin
- Command line
-
hf download hf://idah4/my_first_qa_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/idah4/my_first_qa_model/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 1f72b936b5105b3bd14e664ce9dbbbfb04bdffb771d85535f7a17942d40ffbda
- Size of remote file:
- 4.92 kB
- SHA256:
- cf23788282f3e18c43afcac7de1dd1a3d82906a33f0b45483c0c9365266195f7
路
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