Token Classification
Transformers
Safetensors
English
distilbert
named-entity-recognition
ner
bio
Eval Results (legacy)
Instructions to use Hasanblanka/polygraf-ner-stage3-first-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hasanblanka/polygraf-ner-stage3-first-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Hasanblanka/polygraf-ner-stage3-first-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Hasanblanka/polygraf-ner-stage3-first-model") model = AutoModelForTokenClassification.from_pretrained("Hasanblanka/polygraf-ner-stage3-first-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Hasanblanka/polygraf-ner-stage3-first-model: direct link, hf CLI and curl.
- Browser
- Download file 669 kB
-
https://huggingface.co/Hasanblanka/polygraf-ner-stage3-first-model/resolve/main/tokenizer.json
- Command line
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hf download hf://Hasanblanka/polygraf-ner-stage3-first-model/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Hasanblanka/polygraf-ner-stage3-first-model/resolve/main/tokenizer.json
669 kB
File too large to display, you can check the raw version instead.