Instructions to use chintagunta85/test_ner_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chintagunta85/test_ner_5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="chintagunta85/test_ner_5")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("chintagunta85/test_ner_5") model = AutoModelForTokenClassification.from_pretrained("chintagunta85/test_ner_5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 732c9c717f987a3f742b29e43e03a2b4511725e3f150c02595def4f2335be235
- Size of remote file:
- 3.31 kB
- SHA256:
- 0d8e320ef744f05b4949b2f19cc82706f4b529f65c90f50f5ef4869ab685c4ef
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