Instructions to use MLLM-CL/MRLoRA_Router with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MLLM-CL/MRLoRA_Router with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="MLLM-CL/MRLoRA_Router")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MLLM-CL/MRLoRA_Router", device_map="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 093ef8c4dfe26377394727c6b4368718b927931ba175e2dc8cce9b40d6bdddc8
- Size of remote file:
- 1.65 MB
- SHA256:
- 7382476512015510b6017ae9f7aba2e72cc98c85ed6a0f2c95f6d7d46c865e2e
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