Token Classification
Transformers
ONNX
Safetensors
PEFT
English
bert
ner
legal
legal-bert
nigerian-law
lora
Instructions to use WhiteRoomProdigy/amicus-ner-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WhiteRoomProdigy/amicus-ner-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="WhiteRoomProdigy/amicus-ner-v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("WhiteRoomProdigy/amicus-ner-v2") model = AutoModelForTokenClassification.from_pretrained("WhiteRoomProdigy/amicus-ner-v2", device_map="auto") - PEFT
How to use WhiteRoomProdigy/amicus-ner-v2 with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Download onnx/tokenizer.json from WhiteRoomProdigy/amicus-ner-v2: direct link, hf CLI and curl.
- Browser
- Download file 702 kB
-
https://huggingface.co/WhiteRoomProdigy/amicus-ner-v2/resolve/main/onnx/tokenizer.json
- Command line
-
hf download hf://WhiteRoomProdigy/amicus-ner-v2/onnx/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/WhiteRoomProdigy/amicus-ner-v2/resolve/main/onnx/tokenizer.json
702 kB
File too large to display, you can check the raw version instead.