Instructions to use Vrushali/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vrushali/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Vrushali/model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Vrushali/model") model = AutoModelForTokenClassification.from_pretrained("Vrushali/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d76cf4a158e628164f74b94f77aafeefb8ba932dcaccd6e63c8e3e4d9d60f3a5
- Size of remote file:
- 3.9 kB
- SHA256:
- f73582b8a6fbb8a2246eebb46ddccd54ce65c88397c8537ae129ffded58c60d5
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