Instructions to use KalaiselvanD/mega_08_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KalaiselvanD/mega_08_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KalaiselvanD/mega_08_1")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("KalaiselvanD/mega_08_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 925ce82f71b432ac6f66d4a8859fa750149c9d37893a07db9095a176377bce70
- Size of remote file:
- 29.4 MB
- SHA256:
- abae1dc70fb1a923a85d3a6e2ace37a480f7c803cbbb11fb39ca2d158ce5f9d6
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