Instructions to use Navu45/neon_sd_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Navu45/neon_sd_model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Navu45/neon_sd_model") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Update README.md
Browse files
README.md
CHANGED
|
@@ -11,7 +11,7 @@ tags:
|
|
| 11 |
inference: true
|
| 12 |
---
|
| 13 |
|
| 14 |
-
# LoRA text2image fine-tuning - Navu45/
|
| 15 |
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the Navu45/neon_dreambooth dataset. You can find some example images in the following.
|
| 16 |
|
| 17 |

|
|
|
|
| 11 |
inference: true
|
| 12 |
---
|
| 13 |
|
| 14 |
+
# LoRA text2image fine-tuning - Navu45/neon_sd_model
|
| 15 |
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the Navu45/neon_dreambooth dataset. You can find some example images in the following.
|
| 16 |
|
| 17 |

|