Instructions to use tsuyuan/bart-hubert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tsuyuan/bart-hubert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="tsuyuan/bart-hubert-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("tsuyuan/bart-hubert-base") model = AutoModel.from_pretrained("tsuyuan/bart-hubert-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tsuyuan/bart-hubert-base: direct link, hf CLI and curl.
- Browser
- Download file 561 MB
-
https://huggingface.co/tsuyuan/bart-hubert-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tsuyuan/bart-hubert-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tsuyuan/bart-hubert-base/resolve/main/pytorch_model.bin
561 MB
- Xet hash:
- a06b8c7c76f7d245f79a7cb0412618adf7ab8b56b75e88693dbe89cd7ae7f113
- Size of remote file:
- 561 MB
- SHA256:
- 538d754b59d6d8f746cb11658f357d2427c70079f71919afa705865239da00b8
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