Instructions to use nbroad/deb-base-gc2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nbroad/deb-base-gc2 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="nbroad/deb-base-gc2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("nbroad/deb-base-gc2") model = AutoModelForQuestionAnswering.from_pretrained("nbroad/deb-base-gc2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nbroad/deb-base-gc2: direct link, hf CLI and curl.
- Browser
- Download file 2.67 kB
-
https://huggingface.co/nbroad/deb-base-gc2/resolve/main/training_args.bin
- Command line
-
hf download hf://nbroad/deb-base-gc2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nbroad/deb-base-gc2/resolve/main/training_args.bin
2.67 kB
- Xet hash:
- a7874523cf96e04eb37bdc9ae9a9a7bb3bf4d0c4312218030ceb1c06702c08a8
- Size of remote file:
- 2.67 kB
- SHA256:
- f6a4bcccbedcfb63e894fd1ddd7389c03b5d6de8560dfb7ba28f0b78c2825993
路
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