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", device_map="auto")# 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:
- 5f8b5adb26288fb46282dfc3c9eb0fefa0f6ac7c0fe3ade6380a6fe788de4b9b
- Size of remote file:
- 1.33 GB
- SHA256:
- 378b4125e3fb577d054add743d12d3364dcde99285a3ab0b879bb6548c60fdfe
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