first commit

README.md

@@ -1,11 +1,12 @@
 ---
-title: Stable Diffusion From A Ckpt File
-emoji: 💻
-colorFrom: yellow
-colorTo: indigo
+title: Running Stable Diffusion From A Ckpt File
+emoji: 🥰
+colorFrom: gray
+colorTo: gray
 sdk: gradio
-sdk_version: 4.8.0
+sdk_version: 4.7.1
 app_file: app.py
+models: ["waifu-research-department/Rem"]
 pinned: false
 ---
 

app.py

@@ -0,0 +1,68 @@
+from diffusers import StableDiffusionPipeline
+import torch
+work_around_for_hugging_face_gradio_sdk_bug = "/blob/main/rem_3k.ckpt"
+model_url = "https://huggingface.co/waifu-research-department/Rem" + work_around_for_hugging_face_gradio_sdk_bug
+pipeline = StableDiffusionPipeline.from_single_file(
+    model_url,
+    torch_dtype=torch.float16,
+)
+
+
+
+import gradio as gr 
+
+
+description="""
+
+# running stable diffusion from a ckpt file
+
+## NOTICE ⚠️: 
+- this space does not work rn because it needs GPU, feel free to **clone this space** and set your own with GPU an meet your waifu **ヽ（≧□≦）ノ**
+
+
+if you do not have money (just like me **(┬┬﹏┬┬)** ) you can always :
+* **run the code in your PC** if you have a good GPU a good internet connection (to download the ai model only a 1 time thing)
+* **run the model in the cloud** (colab, and kaggle are good alternatives and they have a pretty good internet connection ) 
+### minimalistic code to run a ckpt model 
+* enable GPU (click runtime thenchange runtime type) 
+* install the following libraries
+```
+!pip install -q diffusers gradio omegaconf
+```
+* **restart your kernal** 👈 (click runtime then click restart session)
+* run the following code
+```python
+
+from diffusers import StableDiffusionPipeline
+import torch
+pipeline = StableDiffusionPipeline.from_single_file(
+    "https://huggingface.co/waifu-research-department/Rem/blob/main/rem_3k.ckpt", # put your model url here
+    torch_dtype=torch.float16,
+).to("cuda")
+
+postive_prompt = "anime girl prompt here"  # 👈 change this
+negative_prompt = "3D" 👈  things you hate here
+image = pipeline(postive_prompt,negative_prompt=negative_prompt).images[0]
+
+image # your image is saved in this PIL variable
+```
+"""
+
+
+log = "GPU available"
+try :
+  pipeline.to("cuda")
+except : 
+  log = "no GPU available"
+
+
+def text2img(positive_prompt,negative_prompt):
+    if log == "no GPU available":
+        image = None
+        return log,image
+    else : 
+        image = pipeline(positive_prompt,negative_prompt=negative_prompt).images[0]
+        log = {"postive_prompt":positive_prompt,"negative_prompt":negative_prompt}
+        return log,image
+
+gr.Interface(text2img,["text","text"],["text","image"],examples=[["rem","3D"]],description=description).launch()

requirements.txt

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+torch 
+diffusers 
+gradio 
+omegaconf
+transformers