Instructions to use dev-analyzer/commit-message-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dev-analyzer/commit-message-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dev-analyzer/commit-message-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dev-analyzer/commit-message-model") model = AutoModelForSequenceClassification.from_pretrained("dev-analyzer/commit-message-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e80c0a77f7eb3b1c2e0b3500ea8455d65e6a0792306eddccc7c2329fbd281ee
- Size of remote file:
- 540 MB
- SHA256:
- 5f907d4e2c1fad7ab3407ff9ac4de3157bbcaca3c7aae8c827b740987bf3e7fb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.