Instructions to use mlimb/merge-qlora-model-base01n with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mlimb/merge-qlora-model-base01n with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("meta-llama/Llama-3.2-11B-Vision-Instruct", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("mlimb/merge-qlora-model-base01n") prompt = "What does this picture show you?" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
merge-qlora-model-base01n

- Prompt
- What does this picture show you?
- Negative Prompt
- What is here?
Model description
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Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for mlimb/merge-qlora-model-base01n
Base model
meta-llama/Llama-3.2-11B-Vision-Instruct