Instructions to use Rocketknight1/checkpoint_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rocketknight1/checkpoint_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Rocketknight1/checkpoint_test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Rocketknight1/checkpoint_test") model = AutoModelForSequenceClassification.from_pretrained("Rocketknight1/checkpoint_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3cbbe3889807c7c20fbbdda9c44bea4e3fe504b4034f361bfcf8d9e1cb44e8bf
- Size of remote file:
- 526 MB
- SHA256:
- 7901904526d6ce8fe6778181894f5280cca9f6c52ea67e7cc35fd579751b7e3b
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