Instructions to use aieng-lab/t5-small_commit-intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aieng-lab/t5-small_commit-intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aieng-lab/t5-small_commit-intent")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aieng-lab/t5-small_commit-intent") model = AutoModelForSequenceClassification.from_pretrained("aieng-lab/t5-small_commit-intent") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2be3df0ca902ca17e471b379f856baa11e13a72a78afee296059561e3ea2923d
- Size of remote file:
- 122 MB
- SHA256:
- 73e0fb6d169f7a67282765f3e548a9cfa6b0bc5c242a6d0fda6cc808a52d30bb
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