Instructions to use ShreyashDhoot/v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ShreyashDhoot/v3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-inpainting", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ShreyashDhoot/v3") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Upload folder using huggingface_hub
Browse files
checkpoints/checkpoint--750/adapter_config.json
CHANGED
|
@@ -34,9 +34,9 @@
|
|
| 34 |
"revision": null,
|
| 35 |
"target_modules": [
|
| 36 |
"to_k",
|
| 37 |
-
"
|
| 38 |
"to_out.0",
|
| 39 |
-
"
|
| 40 |
],
|
| 41 |
"target_parameters": null,
|
| 42 |
"task_type": null,
|
|
|
|
| 34 |
"revision": null,
|
| 35 |
"target_modules": [
|
| 36 |
"to_k",
|
| 37 |
+
"to_q",
|
| 38 |
"to_out.0",
|
| 39 |
+
"to_v"
|
| 40 |
],
|
| 41 |
"target_parameters": null,
|
| 42 |
"task_type": null,
|
checkpoints/checkpoint--750/adapter_model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 12795512
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a55fdeef830fb452f822eb80094774b45b1f33a89ed22a730fd3f540868e6af9
|
| 3 |
size 12795512
|