Instructions to use indexxlim/HanBART_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use indexxlim/HanBART_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="indexxlim/HanBART_base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("indexxlim/HanBART_base") model = AutoModel.from_pretrained("indexxlim/HanBART_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from indexxlim/HanBART_base: direct link, hf CLI and curl.
- Browser
- Download file 569 MB
-
https://huggingface.co/indexxlim/HanBART_base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://indexxlim/HanBART_base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/indexxlim/HanBART_base/resolve/main/pytorch_model.bin
569 MB
- Xet hash:
- ea2e4e3267382ff67d1e3ca1195b199316d4b53f57593d422e6c4416479cfb0f
- Size of remote file:
- 569 MB
- SHA256:
- ee7ba0ba694b91484f8d660997d54f710bd4a791653fb74cdec9f11a5170df44
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