Instructions to use aieng-lab/t5-base_commit-intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aieng-lab/t5-base_commit-intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aieng-lab/t5-base_commit-intent")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aieng-lab/t5-base_commit-intent") model = AutoModelForSequenceClassification.from_pretrained("aieng-lab/t5-base_commit-intent") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fbdd3e33f4dd6b435e32968f1d804ea68f7769645dd8e8d342bd0c3a951a5f4c
- Size of remote file:
- 447 MB
- SHA256:
- b4691c03af9703b4ed13f8e8902e29fbcb120b4cf04ffff3e6737f297c43c9a5
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