Instructions to use yzimmermann/FART with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yzimmermann/FART with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yzimmermann/FART", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yzimmermann/FART") model = AutoModelForSequenceClassification.from_pretrained("yzimmermann/FART", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31516d1a09a740111c28ed67f82e3f826cda05ffc65e0120e3ecbf93869c2770
- Size of remote file:
- 13.7 MB
- SHA256:
- e47585f6b27eaa93b92d45d4b3432f0c4813637405aae6a68e9f1232f4f2fe18
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