Instructions to use Blusque/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Blusque/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Blusque/results")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Blusque/results") model = AutoModelForTokenClassification.from_pretrained("Blusque/results") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8448cc323a8c148e09f1b226440055f88ccd47d0bdf437c2abb6738759159cc2
- Size of remote file:
- 5.3 kB
- SHA256:
- 254d8d413c0918b0fa2dfcdd6d916889dd5a0fee46b9784e6107a0476dfe3144
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