Instructions to use radna/mini_intern_chat_triton with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use radna/mini_intern_chat_triton with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="radna/mini_intern_chat_triton", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("radna/mini_intern_chat_triton", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3325b44ba9d333ae15243623e20c767bd9b8147bd9b6760628691ac1dde37245
- Size of remote file:
- 4.96 GB
- SHA256:
- ceea2c6af60bead02f2d1f7c54fd0195906e59bc496589de8ca603562e586ca7
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