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:
- 15fdbdf7229de1d82cc254fd79a5b661ab236a02b30bfcd16ef5972ed076e623
- Size of remote file:
- 5.18 kB
- SHA256:
- 5c92fe1c8fdfad85982b11f7c4edc6233dded1202dc15a444877334ba9b1eedf
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