Instructions to use llm-wizard/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use llm-wizard/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="llm-wizard/test_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("llm-wizard/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("llm-wizard/test_trainer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f6eb56e15660ceefbef834ed9001857b3d58ec40a2d7d9948c625362313f800
- Size of remote file:
- 5.18 kB
- SHA256:
- 0a9d2a09c8a064ae4593eecee842f2923c5fac75c0b46023b0e9f9551ea2a6a0
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