Instructions to use datleviet/vlsp-comom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use datleviet/vlsp-comom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="datleviet/vlsp-comom")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("datleviet/vlsp-comom") model = AutoModelForTokenClassification.from_pretrained("datleviet/vlsp-comom", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from datleviet/vlsp-comom: direct link, hf CLI and curl.
- Browser
- Download file 538 MB
-
https://huggingface.co/datleviet/vlsp-comom/resolve/main/model.safetensors
- Command line
-
hf download hf://datleviet/vlsp-comom/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/datleviet/vlsp-comom/resolve/main/model.safetensors
538 MB
- Xet hash:
- 234938ea08cd6f9e8c0943a16d30cabcccbf04e388eaf7b11c518cf4f41ec683
- Size of remote file:
- 538 MB
- SHA256:
- 59109d66e0dffbccdfad960e8b0089c07e94ca2df4842dc1f5ced9b8e1c398a7
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