Instructions to use rushikeshwalode/token_classification_NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rushikeshwalode/token_classification_NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="rushikeshwalode/token_classification_NER")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("rushikeshwalode/token_classification_NER") model = AutoModelForTokenClassification.from_pretrained("rushikeshwalode/token_classification_NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from rushikeshwalode/token_classification_NER: direct link, hf CLI and curl.
- Browser
- Download file 266 MB
-
https://huggingface.co/rushikeshwalode/token_classification_NER/resolve/main/model.safetensors
- Command line
-
hf download hf://rushikeshwalode/token_classification_NER/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/rushikeshwalode/token_classification_NER/resolve/main/model.safetensors
266 MB
- Xet hash:
- 15c7901580eed9a92ab2c9b1a8a30f25a611f0d1749bab9318d46b1c557f37a6
- Size of remote file:
- 266 MB
- SHA256:
- 8e1f46f4c4943914886b4b30f2aea6fd083171ba6df1f10413957815c011e5ca
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