Instructions to use Dabid/test3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dabid/test3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Dabid/test3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Dabid/test3") model = AutoModelForSequenceClassification.from_pretrained("Dabid/test3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d883f087f5358cfd44dea5460c2f025d995d7e0a6174ae43865d597df8fcf7c7
- Size of remote file:
- 437 MB
- SHA256:
- 0c652c0507a0d1a7e89a9820171251e01c39879e823b2cee4dfddee652445389
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