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:
- 4355f293bc98fbc0b69f476fc12ac47a4761d0d2fb763eedb36ab7f901becb5b
- Size of remote file:
- 440 MB
- SHA256:
- 5149d0bd7c9f6aecf00c1b6c4e9877f0d293898f5600eab567b7dc146c3fc255
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