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README.md

@@ -1,130 +1,129 @@
----
-title: PBRealistic
-emoji: 🙅🏻
-colorFrom: indigo
-colorTo: green
-sdk: gradio
-sdk_version: 4.36.0
-app_file: app.py
-pinned: true
-license: creativeml-openrail-m
-header: mini
-short_description: Collage Template + Grid + Style
----
-
-
-![alt text](assets/44.png)
-
- 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
-
-Spaces: https://huggingface.co/spaces/prithivMLmods/IMAGINEO-4K
-
-Take Clone : 
-
-    # Make sure you have git-lfs installed (https://git-lfs.com)
-    git lfs install
-    
-    git clone https://huggingface.co/spaces/prithivMLmods/Midjourney
-    
-    # If you want to clone without large files - just their pointers
-    
-    GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/spaces/prithivMLmods/Midjourney
-
-## Sample Images 
-
-
-| ![Image 1](assets/1.png) | ![Image 2](assets/2.png) |
-|-------------------------|-------------------------|
-| ![Image 3](assets/3.png) | ![Image 4](assets/4.png) |
-
-
-
-## Requirements.txt
-
-
-| torch     | diffusers | transformers | safetensors |
-|-----------|-----------|--------------|-------------|
-| accelerate| spaces    | peft         | pillow      |
-
-
-## Requirements Zero
-
-ZeroGPU is a new kind of hardware for Spaces.
-
-It has two goals :
-
-    Provide free GPU access for Spaces
-    Allow Spaces to run on multiple GPUs
-
-This is achieved by making Spaces efficiently hold and release GPUs as needed (as opposed to a classical GPU Space that holds exactly one GPU at any point in time)
-
-ZeroGPU uses Nvidia A100 GPU devices under the hood (40GB of vRAM are available for each workloads)
-
-
-
-![alt text](assets/x.gif)
-
-
-## Compatibility
-
-ZeroGPU Spaces should mostly be compatible with any PyTorch-based GPU Space.
-Compatibility with high level HF libraries like transformers or diffusers is slightly more guaranteed
-That said, ZeroGPU Spaces are not as broadly compatible as classical GPU Spaces and you might still encounter unexpected bugs
-
-Also, for now, ZeroGPU Spaces only works with the Gradio SDK
-
-Supported versions:
-
-    Gradio: 4+
-    PyTorch: All versions from 2.0.0 to 2.2.0
-    Python: 3.10.13
-
-## Usage
-
-In order to make your Space work with ZeroGPU you need to decorate the Python functions that actually require a GPU with @spaces.GPU
-During the time when a decorated function is invoked, the Space will be attributed a GPU, and it will release it upon completion of the function.
-Here is a practical example :
-
-    +import spaces
-    from diffusers import DiffusionPipeline
-    
-    pipe = DiffusionPipeline.from_pretrained(...)
-    pipe.to('cuda')
-    
-    [email protected]
-    def generate(prompt):
-        return pipe(prompt).images
-    
-    gr.Interface(
-        fn=generate,
-        inputs=gr.Text(),
-        outputs=gr.Gallery(),
-    ).launch()
-
-   
-We first import spaces (importing it first might prevent some issues but is not mandatory)
-Then we decorate the generate function by adding a @spaces.GPU line before its definition
-
-## Duration
-
-If you expect your GPU function to take more than 60s then you need to specify a duration param in the decorator like:
-    
-    @spaces.GPU(duration=120)
-    def generate(prompt):
-       return pipe(prompt).images
-
-It will set the maximum duration of your function call to 120s.
-
-You can also specify a duration if you know that your function will take far less than the 60s default.
-
-The lower the duration, the higher priority your Space visitors will have in the queue
-
-
-.
-
-.
-
-.
-@prithivmlmods
-
+---
+title: PBRealistic
+emoji: 🙅🏻
+colorFrom: indigo
+colorTo: green
+sdk: gradio
+sdk_version: 4.37.2
+app_file: app.py
+pinned: true
+license: creativeml-openrail-m
+header: mini
+short_description: Collage Template + Grid + Style
+---
+
+
+![alt text](assets/44.png)
+
+ 
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+Spaces: https://huggingface.co/spaces/prithivMLmods/IMAGINEO-4K
+
+Take Clone : 
+
+    # Make sure you have git-lfs installed (https://git-lfs.com)
+    git lfs install
+    
+    git clone https://huggingface.co/spaces/prithivMLmods/Midjourney
+    
+    # If you want to clone without large files - just their pointers
+    
+    GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/spaces/prithivMLmods/Midjourney
+
+## Sample Images 
+
+
+| ![Image 1](assets/1.png) | ![Image 2](assets/2.png) |
+|-------------------------|-------------------------|
+| ![Image 3](assets/3.png) | ![Image 4](assets/4.png) |
+
+
+
+## Requirements.txt
+
+
+| torch     | diffusers | transformers | safetensors |
+|-----------|-----------|--------------|-------------|
+| accelerate| spaces    | peft         | pillow      |
+
+
+## Requirements Zero
+
+ZeroGPU is a new kind of hardware for Spaces.
+
+It has two goals :
+
+    Provide free GPU access for Spaces
+    Allow Spaces to run on multiple GPUs
+
+This is achieved by making Spaces efficiently hold and release GPUs as needed (as opposed to a classical GPU Space that holds exactly one GPU at any point in time)
+
+ZeroGPU uses Nvidia A100 GPU devices under the hood (40GB of vRAM are available for each workloads)
+
+
+
+![alt text](assets/x.gif)
+
+
+## Compatibility
+
+ZeroGPU Spaces should mostly be compatible with any PyTorch-based GPU Space.
+Compatibility with high level HF libraries like transformers or diffusers is slightly more guaranteed
+That said, ZeroGPU Spaces are not as broadly compatible as classical GPU Spaces and you might still encounter unexpected bugs
+
+Also, for now, ZeroGPU Spaces only works with the Gradio SDK
+
+Supported versions:
+
+    Gradio: 4+
+    PyTorch: All versions from 2.0.0 to 2.2.0
+    Python: 3.10.13
+
+## Usage
+
+In order to make your Space work with ZeroGPU you need to decorate the Python functions that actually require a GPU with @spaces.GPU
+During the time when a decorated function is invoked, the Space will be attributed a GPU, and it will release it upon completion of the function.
+Here is a practical example :
+
+    +import spaces
+    from diffusers import DiffusionPipeline
+    
+    pipe = DiffusionPipeline.from_pretrained(...)
+    pipe.to('cuda')
+    
+    [email protected]
+    def generate(prompt):
+        return pipe(prompt).images
+    
+    gr.Interface(
+        fn=generate,
+        inputs=gr.Text(),
+        outputs=gr.Gallery(),
+    ).launch()
+
+   
+We first import spaces (importing it first might prevent some issues but is not mandatory)
+Then we decorate the generate function by adding a @spaces.GPU line before its definition
+
+## Duration
+
+If you expect your GPU function to take more than 60s then you need to specify a duration param in the decorator like:
+    
+    @spaces.GPU(duration=120)
+    def generate(prompt):
+       return pipe(prompt).images
+
+It will set the maximum duration of your function call to 120s.
+
+You can also specify a duration if you know that your function will take far less than the 60s default.
+
+The lower the duration, the higher priority your Space visitors will have in the queue
+
+
+.
+
+.
+
+.
+@prithivmlmods