Instructions to use Texttra/BhoriKontext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Texttra/BhoriKontext 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("black-forest-labs/FLUX.1-Kontext-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Texttra/BhoriKontext") prompt = "-" 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] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
Update handler.py
Browse files- handler.py +1 -1
handler.py
CHANGED
|
@@ -12,7 +12,7 @@ class EndpointHandler:
|
|
| 12 |
# Load Flux Kontext model
|
| 13 |
self.pipe = FluxKontextPipeline.from_pretrained(
|
| 14 |
"black-forest-labs/FLUX.1-Kontext-dev",
|
| 15 |
-
torch_dtype=torch.
|
| 16 |
)
|
| 17 |
self.pipe.to("cuda" if torch.cuda.is_available() else "cpu")
|
| 18 |
print("✅ Model ready.")
|
|
|
|
| 12 |
# Load Flux Kontext model
|
| 13 |
self.pipe = FluxKontextPipeline.from_pretrained(
|
| 14 |
"black-forest-labs/FLUX.1-Kontext-dev",
|
| 15 |
+
torch_dtype=torch.float32,
|
| 16 |
)
|
| 17 |
self.pipe.to("cuda" if torch.cuda.is_available() else "cpu")
|
| 18 |
print("✅ Model ready.")
|