Instructions to use anubhavmaity/dummy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anubhavmaity/dummy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anubhavmaity/dummy")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anubhavmaity/dummy") model = AutoModelForSequenceClassification.from_pretrained("anubhavmaity/dummy") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 582646ea01d5cdb1d560f9ea7e37292cb03d4e1eed53a81be58f4546f18b9435
- Size of remote file:
- 438 MB
- SHA256:
- 5712fbda81c86523209534886b6efde5dffbd6b812b73dd9d0bb24743b12dc01
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