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 training_args.bin from BoghdadyJR/test-ner: direct link, hf CLI and curl.
- Browser
- Download file 3.9 kB
-
https://huggingface.co/BoghdadyJR/test-ner/resolve/main/training_args.bin
- Command line
-
hf download hf://BoghdadyJR/test-ner/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BoghdadyJR/test-ner/resolve/main/training_args.bin
3.9 kB
- Xet hash:
- 4a77b6ef95203314dab9bad7d32d905863093001e0430269b9cfbe3a04b35f1c
- Size of remote file:
- 3.9 kB
- SHA256:
- 25a3e14417bf546c1e251e84861b4266d9437d71546626586eec705890b4f875
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