Instructions to use jaimik69/bart-base-pubmed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jaimik69/bart-base-pubmed 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="jaimik69/bart-base-pubmed")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("jaimik69/bart-base-pubmed") model = AutoModelForSeq2SeqLM.from_pretrained("jaimik69/bart-base-pubmed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jaimik69/bart-base-pubmed: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/jaimik69/bart-base-pubmed/resolve/6c005f4f21ce9852e32184d866300fba9a7bff8e/training_args.bin
- Command line
-
hf download hf://jaimik69/bart-base-pubmed@6c005f4f21ce9852e32184d866300fba9a7bff8e/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jaimik69/bart-base-pubmed/resolve/6c005f4f21ce9852e32184d866300fba9a7bff8e/training_args.bin
4.98 kB
- Xet hash:
- c354c89a673ced5d55e6be330e31a05b0a658a92d4b2bfa913e609766efb5de0
- Size of remote file:
- 4.98 kB
- SHA256:
- c825ba96fbe50481d15f8586c0385e40be6fd71b28da9c340d1d04d88515ca8c
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