Instructions to use hadiaskari98/Software_NER_prod with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hadiaskari98/Software_NER_prod with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hadiaskari98/Software_NER_prod")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hadiaskari98/Software_NER_prod") model = AutoModelForTokenClassification.from_pretrained("hadiaskari98/Software_NER_prod", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 96c62665f955a2a532f2e9e4c22948a24e507a37fe2875b276aed1ef0119f943
- Size of remote file:
- 1.33 GB
- SHA256:
- e1cab4af7cb8d380b66fb688b75413f5208f81e85a1d545bc40e6dade1275966
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