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add tags and inference example with diffusers (#2)

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- add tags and inference example with diffusers (9f83f192c4bf294179e85eac45ead1a5db40acef)


Co-authored-by: Linoy Tsaban <[email protected]>

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  1. README.md +50 -1
README.md CHANGED
@@ -9,6 +9,55 @@ pipeline_tag: text-to-image
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  tags:
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  - Qwen-Image;
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  - distillation;
 
 
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  ---
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- Please refer to [Qwen-Image-Lightning github](https://github.com/ModelTC/Qwen-Image-Lightning/) to learn how to use the models.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  tags:
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  - Qwen-Image;
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  - distillation;
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+ - LoRA
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+ library_name: diffusers
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  ---
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+ Please refer to [Qwen-Image-Lightning github](https://github.com/ModelTC/Qwen-Image-Lightning/) to learn how to use the models.
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+
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+ use with diffusers 🧨:
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+
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+ make sure to install diffusers from `main` (`pip install git+https://github.com/huggingface/diffusers.git`)
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+ ```
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+ from diffusers import DiffusionPipeline, FlowMatchEulerDiscreteScheduler
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+ import torch
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+ import math
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+
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+ # From https://github.com/ModelTC/Qwen-Image-Lightning/blob/342260e8f5468d2f24d084ce04f55e101007118b/generate_with_diffusers.py#L82C9-L97C10
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+ scheduler_config = {
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+ "base_image_seq_len": 256,
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+ "base_shift": math.log(3), # We use shift=3 in distillation
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+ "invert_sigmas": False,
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+ "max_image_seq_len": 8192,
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+ "max_shift": math.log(3), # We use shift=3 in distillation
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+ "num_train_timesteps": 1000,
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+ "shift": 1.0,
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+ "shift_terminal": None, # set shift_terminal to None
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+ "stochastic_sampling": False,
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+ "time_shift_type": "exponential",
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+ "use_beta_sigmas": False,
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+ "use_dynamic_shifting": True,
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+ "use_exponential_sigmas": False,
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+ "use_karras_sigmas": False,
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+ }
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+ scheduler = FlowMatchEulerDiscreteScheduler.from_config(scheduler_config)
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+ pipe = DiffusionPipeline.from_pretrained(
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+ "Qwen/Qwen-Image", scheduler=scheduler, torch_dtype=torch.bfloat16
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+ ).to("cuda")
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+ pipe.load_lora_weights(
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+ "lightx2v/Qwen-Image-Lightning", weight_name="Qwen-Image-Lightning-8steps-V1.0.safetensors"
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+ )
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+
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+ prompt = "a tiny astronaut hatching from an egg on the moon, Ultra HD, 4K, cinematic composition."
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+ negative_prompt = " "
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+ image = pipe(
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+ prompt=prompt,
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+ negative_prompt=negative_prompt,
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+ width=1024,
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+ height=1024,
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+ num_inference_steps=8,
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+ true_cfg_scale=1.0,
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+ generator=torch.manual_seed(0),
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+ ).images[0]
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+ image.save("qwen_fewsteps.png")
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+ ```