Instructions to use callgg/image-edit-decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use callgg/image-edit-decoder 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("callgg/image-edit-decoder", dtype=torch.bfloat16, device_map="cuda") 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
Download text_encoder/generation_config.json from callgg/image-edit-decoder: direct link, hf CLI and curl.
- Browser
- Download file 244 Bytes
-
https://huggingface.co/callgg/image-edit-decoder/resolve/main/text_encoder/generation_config.json
- Command line
-
hf download hf://callgg/image-edit-decoder/text_encoder/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/callgg/image-edit-decoder/resolve/main/text_encoder/generation_config.json
244 Bytes
| { | |
| "bos_token_id": 151643, | |
| "do_sample": true, | |
| "eos_token_id": [ | |
| 151645, | |
| 151643 | |
| ], | |
| "pad_token_id": 151643, | |
| "repetition_penalty": 1.05, | |
| "temperature": 0.1, | |
| "top_k": 1, | |
| "top_p": 0.001, | |
| "transformers_version": "4.55.2" | |
| } | |