Instructions to use gigant/bart-base-xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gigant/bart-base-xsum with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("gigant/bart-base-xsum") model = AutoModelForSeq2SeqLM.from_pretrained("gigant/bart-base-xsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from gigant/bart-base-xsum: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/gigant/bart-base-xsum/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://gigant/bart-base-xsum/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/gigant/bart-base-xsum/resolve/main/flax_model.msgpack
558 MB
- Xet hash:
- 7683719725e71a269454c6da0dc61743240226f058e64de2fc36dd2b2e341f14
- Size of remote file:
- 558 MB
- SHA256:
- 594b7503f78b7f9e51c6bee421812fe9e769ebfae38de55cbf4298449a706711
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