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")# pip install -U transformers accelerate # 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 pytorch_model.bin from autoevaluate/entity-extraction: direct link, hf CLI and curl.
- Browser
- Download file 266 MB
-
https://huggingface.co/autoevaluate/entity-extraction/resolve/refs%2Fpr%2F8/pytorch_model.bin
- Command line
-
hf download hf://autoevaluate/entity-extraction@refs/pr/8/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/autoevaluate/entity-extraction/resolve/refs%2Fpr%2F8/pytorch_model.bin
266 MB
- Xet hash:
- 9050db1d0a076e25746d7ff95e6c6cc115a0dfc9b1ec0977f687a30208a14277
- Size of remote file:
- 266 MB
- SHA256:
- 48ebb7a89b19b62d0edab1f2814f8202987030f65333d0fea670a8dc00a18e0e
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