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README.md

@@ -1,12 +1,13 @@
----
-title: Flux To Diffusers Zero Test
-emoji: 🚀
-colorFrom: gray
-colorTo: yellow
-sdk: gradio
-sdk_version: 5.22.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: test flux safetensors to diffusers for Zero GPU
+emoji: 🙄
+colorFrom: indigo
+colorTo: purple
+sdk: gradio
+sdk_version: 4.44.0
+app_file: app.py
+pinned: false
+license: mit
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import spaces
+
+@spaces.GPU
+def dummy_gpu():
+    pass
+
+import gradio as gr
+import torch
+from pathlib import Path
+from diffusers import FluxPipeline, FluxTransformer2DModel
+from huggingface_hub import hf_hub_download, HfApi
+
+IS_TURBO = False
+TEMP_DIR = "./temp"
+repo_id = "camenduru/FLUX.1-dev-diffusers"
+#repo_id = "black-forest-labs/FLUX.1-schnell" # if schnell
+#repo_id = "aoxo/flux.1dev-abliteratedv2" # if dev.abl
+dtype = torch.bfloat16
+#cp = hf_hub_download("John6666/flux1-backup-202502", "ultrarealFineTune_v1.safetensors", repo_type="dataset")
+cp = hf_hub_download("John6666/flux1-backup-202502", "jibMixFlux_v8AccentueightNSFW.safetensors", repo_type="dataset")
+transformer = FluxTransformer2DModel.from_single_file(cp, subfolder="transformer", torch_dtype=dtype, config=repo_id)
+pipe = FluxPipeline.from_pretrained(repo_id, transformer=transformer, torch_dtype=dtype)
+
+if IS_TURBO:
+    pipe.to("cuda")
+    pipe.load_lora_weights(hf_hub_download("ByteDance/Hyper-SD", "Hyper-FLUX.1-dev-8steps-lora.safetensors"), adapter_name="hyper-sd")
+    pipe.set_adapters(["hyper-sd"], adapter_weights=[0.125])
+    pipe.fuse_lora()
+    pipe.unload_lora_weights()
+    pipe.to("cpu")
+
+def upload_model(repo_id: str="", token: str="", progress=gr.Progress(track_tqdm=True)):
+    if not token: return "Token not found."
+    pipe.save_pretrained(TEMP_DIR)
+    api = HfApi(token=token if token else False)
+    api.create_repo(repo_id=repo_id, token=token, private=True, exist_ok=True)
+    api.upload_folder(repo_id=repo_id, repo_type="model", folder_path=TEMP_DIR, path_in_repo=".")
+    api.upload_file(repo_id=repo_id, repo_type="model", path_or_fileobj=cp, path_in_repo=Path(cp).name)
+    return ""
+
+with gr.Blocks() as demo:
+    repo_id = gr.Textbox(label="Repo ID", value="")
+    hf_token = gr.Textbox(label="Your HF write token", value="")
+    run_button = gr.Button("Submit", variant="primary")
+    info_md = gr.Markdown("<br><br><br>")
+
+    run_button.click(upload_model, [repo_id, hf_token], [info_md])
+
+demo.launch()

requirements.txt

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+huggingface_hub
+#torch==2.4.0
+#torchvision
+#torchaudio
+torchao==0.9.0
+diffusers==0.32.2
+peft
+transformers==4.48.3
+numpy
+scipy
+Pillow
+sentencepiece
+protobuf
+triton