Instructions to use lsb/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lsb/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lsb/test_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lsb/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("lsb/test_trainer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 884ba826784e7e9512db48ff541a37b57cc70b0163ee92b62002070a67381b34
- Size of remote file:
- 438 MB
- SHA256:
- 56f298cd4cb74c4bca7321f5067577a9f4763e3315681dbdac293a6af2e7df17
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