Instructions to use dtorber/BioNLP-intro-disc-tech-eLife with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/BioNLP-intro-disc-tech-eLife with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" 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("summarization", model="dtorber/BioNLP-intro-disc-tech-eLife")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dtorber/BioNLP-intro-disc-tech-eLife") model = AutoModelForSeq2SeqLM.from_pretrained("dtorber/BioNLP-intro-disc-tech-eLife", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dtorber/BioNLP-intro-disc-tech-eLife: direct link, hf CLI and curl.
- Browser
- Download file 4.35 kB
-
https://huggingface.co/dtorber/BioNLP-intro-disc-tech-eLife/resolve/b6087bd1faa8dce72ca3900a3e4a91db6fc65ea5/training_args.bin
- Command line
-
hf download hf://dtorber/BioNLP-intro-disc-tech-eLife@b6087bd1faa8dce72ca3900a3e4a91db6fc65ea5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dtorber/BioNLP-intro-disc-tech-eLife/resolve/b6087bd1faa8dce72ca3900a3e4a91db6fc65ea5/training_args.bin
4.35 kB
- Xet hash:
- 54ba193f4f07e69baa2b33f0c8ca4e20cfe031b365b3fb6abde5849a545d7bb6
- Size of remote file:
- 4.35 kB
- SHA256:
- 6e99541b60b39e773277619a49ce3433dbece0abd6b163ddb465881e020e7f9e
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