Instructions to use PeterBanning71/bart-large-finetuned-eLife with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PeterBanning71/bart-large-finetuned-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="PeterBanning71/bart-large-finetuned-eLife")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("PeterBanning71/bart-large-finetuned-eLife") model = AutoModelForSeq2SeqLM.from_pretrained("PeterBanning71/bart-large-finetuned-eLife", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from PeterBanning71/bart-large-finetuned-eLife: direct link, hf CLI and curl.
- Browser
- Download file 1.63 GB
-
https://huggingface.co/PeterBanning71/bart-large-finetuned-eLife/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://PeterBanning71/bart-large-finetuned-eLife/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/PeterBanning71/bart-large-finetuned-eLife/resolve/main/pytorch_model.bin
1.63 GB
- Xet hash:
- 760a60603035acfa56e70bb624611bbf2be4e4e4abdf5fa60955e2b1859a6e3b
- Size of remote file:
- 1.63 GB
- SHA256:
- b48c74d1373f961da95625fa65522831093aa601b78d59d57a8e56dbe6e86df3
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