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1from diffusers import FluxPipeline
2import torch
3
4# Charger le pipeline avec le modèle fine-tuné
5pipe = FluxPipeline.from_pretrained(
6 "ludoveltz/pub-180",
7 torch_dtype=torch.bfloat16,
8 device_map="auto"
9)
10
11# Générer une image publicitaire
12prompt = "Une publicité élégante pour un parfum de luxe, bouteille en cristal, éclairage dramatique, fond noir sophistiqué"
13
14image = pipe(
15 prompt=prompt,
16 width=1024,
17 height=1024,
18 num_inference_steps=28,
19 guidance_scale=7.5
20).images[0]
21
22image.save("pub_image.png")1import requests
2
3headers = {
4 "Authorization": "Bearer YOUR_HF_TOKEN",
5 "Content-Type": "application/json"
6}
7
8payload = {
9 "inputs": "Une publicité élégante pour un parfum de luxe",
10 "parameters": {
11 "width": 1024,
12 "height": 1024,
13 "num_inference_steps": 28,
14 "guidance_scale": 7.5
15 }
16}
17
18response = requests.post(
19 "https://api-inference.huggingface.co/models/ludoveltz/pub-180",
20 json=payload,
21 headers=headers
22)
23
24with open("generated_ad.png", "wb") as f:
25 f.write(response.content)