Instructions to use imgreencucumber/rubert-ner-collection3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use imgreencucumber/rubert-ner-collection3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="imgreencucumber/rubert-ner-collection3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("imgreencucumber/rubert-ner-collection3") model = AutoModelForTokenClassification.from_pretrained("imgreencucumber/rubert-ner-collection3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload from https://github.com/imgreencucumber/ru-ner/commit/3da1f09c15be1c18a1907fba2b72f800c6e49d0e
bf9a7fa verified Download tokenizer.json from imgreencucumber/rubert-ner-collection3: direct link, hf CLI and curl.
- Browser
- Download file 3.57 MB
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https://huggingface.co/imgreencucumber/rubert-ner-collection3/resolve/main/tokenizer.json
- Command line
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hf download hf://imgreencucumber/rubert-ner-collection3/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/imgreencucumber/rubert-ner-collection3/resolve/main/tokenizer.json
3.57 MB
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