Token Classification
Transformers
PyTorch
Graphcore
roberta
Generated from Trainer
Eval Results (legacy)
Instructions to use jimypbr/test-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jimypbr/test-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jimypbr/test-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jimypbr/test-ner") model = AutoModelForTokenClassification.from_pretrained("jimypbr/test-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download vocab.json from jimypbr/test-ner: direct link, hf CLI and curl.
- Browser
- Download file 798 kB
-
https://huggingface.co/jimypbr/test-ner/resolve/main/vocab.json
- Command line
-
hf download hf://jimypbr/test-ner/vocab.json
-
curl -L -o vocab.json https://huggingface.co/jimypbr/test-ner/resolve/main/vocab.json
798 kB
File too large to display, you can check the raw version instead.