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:
- 823ca2766050e74e5d7dce1d2ebba52a27be4bcb6a55b64fe7cd4f79c9cf9e80
- Size of remote file:
- 3.39 kB
- SHA256:
- fb10f6e4b7f501a613c217780a945534fb3e9d4ac2dbcae508c7d94cba536f08
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