Instructions to use cahya/bart-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cahya/bart-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cahya/bart-base") model = AutoModelForSeq2SeqLM.from_pretrained("cahya/bart-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from cahya/bart-base: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/cahya/bart-base/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://cahya/bart-base/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/cahya/bart-base/resolve/main/flax_model.msgpack
558 MB
- Xet hash:
- 6338a9b4ba6d28a37e4e9f06ab5735258890edcdcc0340c0883a4f84e9063d91
- Size of remote file:
- 558 MB
- SHA256:
- baaec01de69d4a024b20b1be62c50017779bdfed0d9c24ad54597412cab22a8f
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