Instructions to use Vrushali/model_abv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vrushali/model_abv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Vrushali/model_abv")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Vrushali/model_abv") model = AutoModelForTokenClassification.from_pretrained("Vrushali/model_abv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bf156073744993866bb2db0ce49eb008cc9b4a25957c2f503a04f153eeea94de
- Size of remote file:
- 3.9 kB
- SHA256:
- 61e3d2d9317b53a1086c769186bc6a17afb84f1e2a74985311dc0c258ca4ab16
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