Instructions to use dtorber/BioNLP-intro-disc-tech-decoder-PLOS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/BioNLP-intro-disc-tech-decoder-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-tech-decoder-PLOS")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dtorber/BioNLP-intro-disc-tech-decoder-PLOS") model = AutoModelForSeq2SeqLM.from_pretrained("dtorber/BioNLP-intro-disc-tech-decoder-PLOS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dtorber/BioNLP-intro-disc-tech-decoder-PLOS: direct link, hf CLI and curl.
- Browser
- Download file 4.35 kB
-
https://huggingface.co/dtorber/BioNLP-intro-disc-tech-decoder-PLOS/resolve/main/training_args.bin
- Command line
-
hf download hf://dtorber/BioNLP-intro-disc-tech-decoder-PLOS/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dtorber/BioNLP-intro-disc-tech-decoder-PLOS/resolve/main/training_args.bin
4.35 kB
- Xet hash:
- b306bd3766cdeb3c80da5012736fdd796cc4adfa48227ad4e3e573d5b5a45727
- Size of remote file:
- 4.35 kB
- SHA256:
- bb2deff2cece8f325cd764fb56e8c5afb873c7b2fe0365ee398fe216748eaaea
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