Instructions to use Adilmar/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Adilmar/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Adilmar/test_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Adilmar/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("Adilmar/test_trainer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eb43ff2b1dedb0b8df5161278aad9bce700046c6b4475fcce45a38d7a5f8089f
- Size of remote file:
- 4.34 kB
- SHA256:
- d70d21f0ba21ac7ffc769259a431480c9efd93cff8f9a0c617d0ea77434afe73
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