Update app.py

app.py

@@ -9,14 +9,14 @@ from transformers import CLIPTextModel, CLIPTokenizer,T5EncoderModel, T5Tokenize
 dtype = torch.bfloat16
 device = "cuda"
 
-bfl_repo = "black-forest-labs/FLUX.1-schnell"
-scheduler = FlowMatchEulerDiscreteScheduler.from_pretrained(bfl_repo, subfolder="scheduler", revision="refs/pr/1")
+bfl_repo = "UnfilteredAI/NSFW-Flux-v1"
+scheduler = FlowMatchEulerDiscreteScheduler.from_pretrained(bfl_repo, subfolder="scheduler", revision="main")
 text_encoder = CLIPTextModel.from_pretrained("openai/clip-vit-large-patch14", torch_dtype=dtype)
 tokenizer = CLIPTokenizer.from_pretrained("openai/clip-vit-large-patch14", torch_dtype=dtype)
-text_encoder_2 = T5EncoderModel.from_pretrained(bfl_repo, subfolder="text_encoder_2", torch_dtype=dtype, revision="refs/pr/1")
-tokenizer_2 = T5TokenizerFast.from_pretrained(bfl_repo, subfolder="tokenizer_2", torch_dtype=dtype, revision="refs/pr/1")
+text_encoder_2 = T5EncoderModel.from_pretrained(bfl_repo, subfolder="text_encoder_2", torch_dtype=dtype, revision="main")
+tokenizer_2 = T5TokenizerFast.from_pretrained(bfl_repo, subfolder="tokenizer_2", torch_dtype=dtype, revision="main")
 vae = AutoencoderKL.from_pretrained(bfl_repo, subfolder="vae", torch_dtype=dtype, revision="refs/pr/1")
-transformer = FluxTransformer2DModel.from_pretrained(bfl_repo, subfolder="transformer", torch_dtype=dtype, revision="refs/pr/1")
+transformer = FluxTransformer2DModel.from_pretrained(bfl_repo, subfolder="transformer", torch_dtype=dtype, revision="main")
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
@@ -64,9 +64,7 @@ css="""
 with gr.Blocks(css=css) as demo:
     
     with gr.Column(elem_id="col-container"):
-        gr.Markdown(f"""# FLUX.1 [schnell]
-12B param rectified flow transformer distilled from [FLUX.1 [pro]](https://blackforestlabs.ai/) for 4 step generation
-[[blog](https://blackforestlabs.ai/2024/07/31/announcing-black-forest-labs/)] [[model](https://huggingface.co/black-forest-labs/FLUX.1-schnell)]
+        gr.Markdown(f"""NSFW-Flux-v1 is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions. Finetuned by UnfilteredAI, this model is designed to produce a wide range of images, including explicit and NSFW (Not Safe For Work) images from textual inputs
         """)
         
         with gr.Row():