Instructions to use barry556652/LoRAtest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use barry556652/LoRAtest with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("barry556652/LoRAtest") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
YAML Metadata Error:"base_model" with value "/root/notebooks/nfs/work/barry.chen/diffusers/examples/text_to_image/model/F1210_L2016_5000" is not valid. Use a model id from https://hf.co/models.
LoRA text2image fine-tuning - https://huggingface.co/barry556652/LoRAtest
These are LoRA adaption weights for /root/notebooks/nfs/work/barry.chen/diffusers/examples/text_to_image/model/F1210_L2016_5000. The weights were fine-tuned on the barry556652/broke dataset. You can find some example images in the following.
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