Instructions to use BoghdadyJR/test-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BoghdadyJR/test-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="BoghdadyJR/test-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("BoghdadyJR/test-ner") model = AutoModelForTokenClassification.from_pretrained("BoghdadyJR/test-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from BoghdadyJR/test-ner: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/BoghdadyJR/test-ner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://BoghdadyJR/test-ner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/BoghdadyJR/test-ner/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- 5434dd0d67461a1c2ef82938f9c8de7c69f076a2327c9ea1090a2fcf06091e24
- Size of remote file:
- 431 MB
- SHA256:
- a8f040086667e06888687c82c0e3682ed62f8c6ddcbab914092b477243edb2de
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