Instructions to use panigrah/wineberto-labels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use panigrah/wineberto-labels with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="panigrah/wineberto-labels")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("panigrah/wineberto-labels") model = AutoModelForTokenClassification.from_pretrained("panigrah/wineberto-labels", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c47bbb055639d1f2e438b0b6c9c223f015daab8683c9f3d1903c112bc17d9407
- Size of remote file:
- 436 MB
- SHA256:
- 16e891ffe486c8eb792da728e84654f0f8f089f2d84f8184f12a4ffd6d550743
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