Instructions to use gjonesQ02/TestFinedTunedModel_A with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gjonesQ02/TestFinedTunedModel_A 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="gjonesQ02/TestFinedTunedModel_A")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("gjonesQ02/TestFinedTunedModel_A") model = AutoModelForQuestionAnswering.from_pretrained("gjonesQ02/TestFinedTunedModel_A", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gjonesQ02/TestFinedTunedModel_A: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/gjonesQ02/TestFinedTunedModel_A/resolve/main/training_args.bin
- Command line
-
hf download hf://gjonesQ02/TestFinedTunedModel_A/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gjonesQ02/TestFinedTunedModel_A/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- ec678a70c98f2b48aa82688fa0f4b91dfd88780086d9dc3a8b5329e0b7cdec4b
- Size of remote file:
- 4.73 kB
- SHA256:
- d409c2a0ef25c027cd133b1f9c78194bded27ec7003ea9067d8082deb82ae723
路
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