Instructions to use chosenone80/model_save with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chosenone80/model_save with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="chosenone80/model_save")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("chosenone80/model_save") model = AutoModelForTokenClassification.from_pretrained("chosenone80/model_save", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ba2f2e99c64d323ac4579b14375df07d3d015a6d4fcd30a86e518389eeeda79
- Size of remote file:
- 434 MB
- SHA256:
- 823503901da329ca9699e31349514faee95271163a3e785911c3c812fd8572fe
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