Delete Fluently-XL-v2.py

Fluently-XL-v2.py

@@ -1,47 +0,0 @@
-# https://huggingface.co/spaces/ehristoforu/dalle-3-xl-lora-v2
-# pip install diffusers transformers accelerate safetensors
-# HF_ENDPOINT=https://hf-mirror.com python Fluently-XL-v2.py
-
-import torch
-from diffusers import StableDiffusionXLPipeline, EulerAncestralDiscreteScheduler
-
-model_id = "fluently/Fluently-XL-v2"
-negative_prompt = "(deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, (NSFW:1.25)"
-width, height = 1024, 1024
-guidance_scale = 6
-
-def save_image(img):
-    import uuid
-    unique_name = str(uuid.uuid4()) + ".png"
-    img.save(unique_name)
-    return unique_name
-
-def t2i(prompt):
-        
-    pipe = StableDiffusionXLPipeline.from_pretrained(model_id, torch_dtype=torch.float16, use_safetensors=True,)
-    pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
-
-    ## lora
-    # pipe.load_lora_weights("ehristoforu/dalle-3-xl-v2", weight_name="dalle-3-xl-lora-v2.safetensors", adapter_name="dalle")
-    # pipe.set_adapters("dalle")
-
-    pipe.to("cuda")
-
-    image = pipe(
-        prompt=prompt,
-        negative_prompt=negative_prompt,
-        width=width,
-        height=height,
-        guidance_scale=guidance_scale,
-        num_inference_steps=25,
-        num_images_per_prompt=1,
-        cross_attention_kwargs={"scale": 0.65},
-        output_type="pil",
-    ).images[0]
-
-    return image
-
-if __name__ == "__main__":
-    prompt = "a girl in beijing"
-    image = t2i(prompt)
-    image.save("fluently-xl-v2_output.png")