Instructions to use rach405/test_trainer6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rach405/test_trainer6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rach405/test_trainer6")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rach405/test_trainer6") model = AutoModelForSequenceClassification.from_pretrained("rach405/test_trainer6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9bd8dcd78e5453da6ae69846380b5aecc2221f2c7aee373feda30117ef7ae78c
- Size of remote file:
- 433 MB
- SHA256:
- cd40346dea7f0187055ee5d79349336f7b330bb48edae6c3894da02848a22740
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