Instructions to use macavaney/deepct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use macavaney/deepct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="macavaney/deepct")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("macavaney/deepct") model = AutoModelForTokenClassification.from_pretrained("macavaney/deepct", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (67c243174e472e0e3cce955ac2d41ba529dbf6a2) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>913f6ed
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initial commit
Sean MacAvaney1f3d61a -
initial commit
Sean MacAvaneya8d68c2