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Instructions to use Vagabondworker/Vaga with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use Vagabondworker/Vaga with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("undefined") model.load_adapter("Vagabondworker/Vaga", set_active=True) - Diffusers
How to use Vagabondworker/Vaga with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("XLabs-AI/flux-RealismLora,mattshumer/Reflection-Llama-3.1-70B,MikeRoz/mattshumer_Reflection-Llama-3.1-70B-8.0bpw-h8-exl2,meta-llama/Meta-Llama-3.1-8B-Instruct,Downtown-Case/meta-llama_Meta-Llama-3.1-8B-Instruct-exl2-8bpw", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Vagabondworker/Vaga") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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