Instructions to use ben-epstein/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ben-epstein/output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ben-epstein/output")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ben-epstein/output") model = AutoModelForTokenClassification.from_pretrained("ben-epstein/output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c1bbf4d2f6bdccd66ca5d46da621c9b6ba287f8388b1bd4d120e7700ee21c86
- Size of remote file:
- 261 MB
- SHA256:
- 3f16d70e0ea311126466f97447f4006fbae8c30062dcb9b7a9833778616e74c2
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