Instructions to use gjonesQ02/testLLMModels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gjonesQ02/testLLMModels 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/testLLMModels")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("gjonesQ02/testLLMModels") model = AutoModelForQuestionAnswering.from_pretrained("gjonesQ02/testLLMModels", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gjonesQ02/testLLMModels: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/gjonesQ02/testLLMModels/resolve/main/training_args.bin
- Command line
-
hf download hf://gjonesQ02/testLLMModels/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gjonesQ02/testLLMModels/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- 5b1c2210bc1c96a94f254c17607a3194979f8ecc7df0546c1ce26c186510b280
- Size of remote file:
- 4.66 kB
- SHA256:
- 919a16a65397f9f20e2d87ed0dff5c1566938f63abfbf776f4ee5a8c1c3370d7
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