Instructions to use dtorber/BioNLP-intro-disc-eLife with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/BioNLP-intro-disc-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-eLife")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dtorber/BioNLP-intro-disc-eLife") model = AutoModelForSeq2SeqLM.from_pretrained("dtorber/BioNLP-intro-disc-eLife", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dtorber/BioNLP-intro-disc-eLife: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/dtorber/BioNLP-intro-disc-eLife/resolve/main/training_args.bin
- Command line
-
hf download hf://dtorber/BioNLP-intro-disc-eLife/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dtorber/BioNLP-intro-disc-eLife/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- cd7367a1ef32415dbea25c13b5b673ac4735b9c2030c15a02cec56d8379d12ff
- Size of remote file:
- 5.24 kB
- SHA256:
- a0817b276cad03e7066377612770e014a5d07a4c1a3b6771482351c6afaa34b6
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