Instructions to use dtorber/BioNLP-intro-disc-PLOS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/BioNLP-intro-disc-PLOS 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-PLOS")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dtorber/BioNLP-intro-disc-PLOS") model = AutoModelForSeq2SeqLM.from_pretrained("dtorber/BioNLP-intro-disc-PLOS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dtorber/BioNLP-intro-disc-PLOS: direct link, hf CLI and curl.
- Browser
- Download file 4.35 kB
-
https://huggingface.co/dtorber/BioNLP-intro-disc-PLOS/resolve/main/training_args.bin
- Command line
-
hf download hf://dtorber/BioNLP-intro-disc-PLOS/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dtorber/BioNLP-intro-disc-PLOS/resolve/main/training_args.bin
4.35 kB
- Xet hash:
- 22bc9eccb2f74a0a46096ba766e1f1b448241097e7848b7154781f56e3c593f6
- Size of remote file:
- 4.35 kB
- SHA256:
- cc4f6d2010c38648744f276d2ffbd8ca433c83beaba654e798d5bc042e52051d
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