Instructions to use dtorber/BioNLP-tech-decoder-eLife with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/BioNLP-tech-decoder-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-tech-decoder-eLife")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dtorber/BioNLP-tech-decoder-eLife") model = AutoModelForSeq2SeqLM.from_pretrained("dtorber/BioNLP-tech-decoder-eLife", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download vocab.json from dtorber/BioNLP-tech-decoder-eLife: direct link, hf CLI and curl.
- Browser
- Download file 798 kB
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https://huggingface.co/dtorber/BioNLP-tech-decoder-eLife/resolve/main/vocab.json
- Command line
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hf download hf://dtorber/BioNLP-tech-decoder-eLife/vocab.json
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curl -L -o vocab.json https://huggingface.co/dtorber/BioNLP-tech-decoder-eLife/resolve/main/vocab.json
798 kB
File too large to display, you can check the raw version instead.