Token Classification
Transformers
PyTorch
English
roberta
feature-extraction
entity-recognition
foundation-model
RoBERTa
generic
Instructions to use numind/NuNER-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use numind/NuNER-v0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="numind/NuNER-v0.1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("numind/NuNER-v0.1") model = AutoModel.from_pretrained("numind/NuNER-v0.1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from numind/NuNER-v0.1: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/numind/NuNER-v0.1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://numind/NuNER-v0.1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/numind/NuNER-v0.1/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- a3d81f3aba8b8571f91db8d2f8ad877ac7e1436fbaa735a6d3c59cf7b5f6eae6
- Size of remote file:
- 499 MB
- SHA256:
- 54819285a67e855b490e480bd3c48e5c5ca84144a670d763611e30378153c583
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