Instructions to use mirikwa/gro-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mirikwa/gro-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mirikwa/gro-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mirikwa/gro-ner") model = AutoModelForTokenClassification.from_pretrained("mirikwa/gro-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from mirikwa/gro-ner: direct link, hf CLI and curl.
- Browser
- Download file 875 MB
-
https://huggingface.co/mirikwa/gro-ner/resolve/main/optimizer.pt
- Command line
-
hf download hf://mirikwa/gro-ner/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/mirikwa/gro-ner/resolve/main/optimizer.pt
875 MB
- Xet hash:
- 67c8b4575f2732cfc37dfc5f2a1a7f1c10856b0755afe9ef4d1f2cef64b73224
- Size of remote file:
- 875 MB
- SHA256:
- eb219ddda4faa4a081dd9ff86364f2c363621e0abd92ee8a69ea9d7369e2a02b
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