Instructions to use YChang1112/basis_extraction_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YChang1112/basis_extraction_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="YChang1112/basis_extraction_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("YChang1112/basis_extraction_model") model = AutoModelForTokenClassification.from_pretrained("YChang1112/basis_extraction_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from YChang1112/basis_extraction_model: direct link, hf CLI and curl.
- Browser
- Download file 532 MB
-
https://huggingface.co/YChang1112/basis_extraction_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YChang1112/basis_extraction_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YChang1112/basis_extraction_model/resolve/main/pytorch_model.bin
532 MB
- Xet hash:
- df7ecd66c33556f9fa7a8ec91403735d89bf05b6db59331af191c2c1c18ccebc
- Size of remote file:
- 532 MB
- SHA256:
- 042e863b80f4b269ab929cc41324916aeeb47ff830565158327eaf783d2385e3
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