Instructions to use 9au5a/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 9au5a/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="9au5a/test_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("9au5a/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("9au5a/test_trainer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5388afb04093f598f757134ea730845ac8f8fe600023f2fd1bffd15f99f312ad
- Size of remote file:
- 433 MB
- SHA256:
- f0d1380367532f2e41a11056f6a6c6c78ed7a6249ecf9bc7c8d0d34088870436
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