Token Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
Instructions to use autoevaluate/entity-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autoevaluate/entity-extraction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="autoevaluate/entity-extraction")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("autoevaluate/entity-extraction") model = AutoModelForTokenClassification.from_pretrained("autoevaluate/entity-extraction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from autoevaluate/entity-extraction: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/autoevaluate/entity-extraction/resolve/refs%2Fpr%2F2/tokenizer.json
- Command line
-
hf download hf://autoevaluate/entity-extraction@refs/pr/2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/autoevaluate/entity-extraction/resolve/refs%2Fpr%2F2/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.