Instructions to use marcchew/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcchew/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcchew/test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcchew/test") model = AutoModelForSequenceClassification.from_pretrained("marcchew/test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f272a43115611fcf10c979a986e7baadd2e36f52fa13269703e093e428a267a8
- Size of remote file:
- 438 MB
- SHA256:
- 9a539908fd4d3f16a7f7a6c1e0d21763cee3a610a5becde767634ef74b5f43a5
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