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:
- 6d254fe06809ffab541a992604ddc8f67a73f0e443b2e52f55dba42e32905de8
- Size of remote file:
- 440 MB
- SHA256:
- 2f5b2c3567d1d874df1985c5b4ad4a51e1860dbeae221109ca473b79883ec64c
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