Instructions to use aloxatel/AVG with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aloxatel/AVG with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aloxatel/AVG")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aloxatel/AVG") model = AutoModelForSequenceClassification.from_pretrained("aloxatel/AVG", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4622d6b5b11bfe56cda945578b26eb547600a1efbed42ade7e0fc9902695447e
- Size of remote file:
- 1.32 kB
- SHA256:
- e9522c7430751e463fb4f20aa7744eb92438ee371a259355a94148bb6aec2863
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