Instructions to use Shadman-Rohan/output_diff_approach with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shadman-Rohan/output_diff_approach with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Shadman-Rohan/output_diff_approach")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Shadman-Rohan/output_diff_approach") model = AutoModelForTokenClassification.from_pretrained("Shadman-Rohan/output_diff_approach") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b33e418684a722cd11d28ae802fe3697021c4c9f9e8f0a2a4cd039fdc159ea1b
- Size of remote file:
- 440 MB
- SHA256:
- 3fdb504a7630289a54c2854b4ef983955c0f62f9bbc4f0ba864753acc0352359
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