Instructions to use dayvidwang/spanish_ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dayvidwang/spanish_ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dayvidwang/spanish_ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dayvidwang/spanish_ner") model = AutoModelForTokenClassification.from_pretrained("dayvidwang/spanish_ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dayvidwang/spanish_ner: direct link, hf CLI and curl.
- Browser
- Download file 261 MB
-
https://huggingface.co/dayvidwang/spanish_ner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dayvidwang/spanish_ner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dayvidwang/spanish_ner/resolve/main/pytorch_model.bin
261 MB
- Xet hash:
- b3f91c2d9c314a5919d660b4fd392c7be66795010a13035f650019e62213444c
- Size of remote file:
- 261 MB
- SHA256:
- e33cf385921c646dc9c48a8487a0663ac0b5e7c6d09305995328066b40f21c4b
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