Instructions to use Jit2024/QwenImageEdit-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jit2024/QwenImageEdit-4bit with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Jit2024/QwenImageEdit-4bit", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download text_encoder/generation_config.json from Jit2024/QwenImageEdit-4bit: direct link, hf CLI and curl.
- Browser
- Download file 256 Bytes
-
https://huggingface.co/Jit2024/QwenImageEdit-4bit/resolve/main/text_encoder/generation_config.json
- Command line
-
hf download hf://Jit2024/QwenImageEdit-4bit/text_encoder/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/Jit2024/QwenImageEdit-4bit/resolve/main/text_encoder/generation_config.json
256 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": "4.57.1" | |
| } |