Instructions to use Frorozcol/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Frorozcol/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Frorozcol/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Frorozcol/results") model = AutoModelForSequenceClassification.from_pretrained("Frorozcol/results") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc5847628a646cda66d2784a0db4041ebea8de79ddb39df765d808465e7ecd3d
- Size of remote file:
- 46.8 MB
- SHA256:
- 287a721123004c8d73c220ae75a7e6b149cf0be72e47e01c77e97b730ce43f39
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