ModelNotFound / OSError / RepositoryNotFound

import torch
from diffusers import StableDiffusionXLPipeline
import os

# BROKEN: No authentication, wrong model ID format
model_id = 'my-model'  # Should be 'username/my-model' or official name
pipe = StableDiffusionXLPipeline.from_pretrained(
    model_id,
    torch_dtype=torch.float16,
    use_safetensors=True
)
# ^ This will fail with RepositoryNotFound 404 or 401

image = pipe('a beautiful sunset').images[0]

import torch
from diffusers import StableDiffusionXLPipeline
from huggingface_hub import RepositoryNotFound
import os
import time

# FIXED: Set token, use correct model ID, add retry logic
os.environ['HUGGINGFACE_TOKEN'] = os.getenv('HUGGINGFACE_TOKEN')  # Load from env

model_id = 'stabilityai/stable-diffusion-xl-base-1.0'  # Correct official model ID
max_retries = 3
retry_delay = 5

pipe = None
for attempt in range(max_retries):
    try:
        pipe = StableDiffusionXLPipeline.from_pretrained(
            model_id,
            torch_dtype=torch.float16,
            use_safetensors=True,
            token=os.environ.get('HUGGINGFACE_TOKEN')  # Pass token explicitly
        )
        print(f'✓ Model loaded successfully: {model_id}')
        break
    except RepositoryNotFound as e:
        print(f'✗ Model not found (attempt {attempt + 1}/{max_retries}): {e}')
        if attempt < max_retries - 1:
            print(f'  Retrying in {retry_delay}s...')
            time.sleep(retry_delay)
        else:
            print(f'✗ Failed to load {model_id}. Check model ID, token, and Hub status.')
            raise
    except Exception as e:
        print(f'✗ Unexpected error: {type(e).__name__}: {e}')
        raise

if pipe:
    image = pipe('a beautiful sunset').images[0]
    print('✓ Image generation successful')