Update app.py

app.py

@@ -63,7 +63,7 @@ class HFEmbedder(nn.Module):
     
 
 device = "cuda"
-t5 = HFEmbedder("silveroxides/t5xxl_flan_enc", max_length=512, torch_dtype=torch.float16).to(device)
+t5 = HFEmbedder("silveroxides/t5xxl_flan_enc", max_length=512, torch_dtype=torch.bfloat16).to(device)
 clip = HFEmbedder("silveroxides/clip-vit-large-patch14", max_length=77, torch_dtype=torch.bfloat16).to(device)
 ae = AutoencoderKL.from_pretrained("black-forest-labs/FLUX.1-dev", subfolder="vae", torch_dtype=torch.bfloat16).to(device)
 # quantize(t5, weights=qfloat8)
@@ -743,7 +743,7 @@ def get_image(image) -> torch.Tensor | None:
 from huggingface_hub import hf_hub_download
 from safetensors.torch import load_file
 
-sd = load_file(hf_hub_download(repo_id="lllyasviel/flux1-dev-bnb-nf4", filename="flux1-dev-bnb-nf4-v2.safetensors"))
+sd = load_file(hf_hub_download(repo_id="silveroxides/flux1-nf4-unet", filename="chromafur-alpha_diffusion_model-nf4.safetensors"))
 sd = {k.replace("model.diffusion_model.", ""): v for k, v in sd.items() if "model.diffusion_model" in k}
 model = Flux().to(dtype=torch.bfloat16, device="cuda")
 result = model.load_state_dict(sd)