Instructions to use hucruz/datos-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hucruz/datos-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hucruz/datos-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hucruz/datos-ner") model = AutoModelForTokenClassification.from_pretrained("hucruz/datos-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hucruz/datos-ner: direct link, hf CLI and curl.
- Browser
- Download file 267 MB
-
https://huggingface.co/hucruz/datos-ner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hucruz/datos-ner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hucruz/datos-ner/resolve/main/pytorch_model.bin
267 MB
- Xet hash:
- 01c34f55b1096dbb5154fd3b1672aeb5666a3950ba7b7b919948b4ab0842c081
- Size of remote file:
- 267 MB
- SHA256:
- 4002bd29a018c75f63c4ddb087b2d8eea4745f72f2c4bc32b4794828c904acde
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