First model version

README.md

@@ -1,4 +1,76 @@
 ---
-library_name: diffusers
-pipeline_tag: text-to-image
----
+license: creativeml-openrail-m
+language:
+- en
+tags:
+- stable-diffusion
+- stable-diffusion-diffusers
+- text-to-image
+- safetensors
+- diffusers
+- artwork
+- HDR photography
+- safetensors
+- photos 
+inference: true
+---
+
+# Foto Assisted Diffusion (FAD)_V0 
+
+This model is meant to mimic a modern HDR photography style
+
+It was trained on 600 HDR images on SD1.5 and works best at **768x768** resolutions
+
+Merged with one of my own models for illustrations and drawings, to increase flexibility
+
+# Features:
+* **No additional licensing** 
+ * **Multi-resolution support**
+* **HDR photographic outputs**
+* **No Hi-Res fix required**
+* [**Spreadsheet with supported resolutions, keywords for prompting and other useful hints/tips**](https://docs.google.com/spreadsheets/d/1RGRLZhgiFtLMm5Pg8qK0YMc6wr6uvj9-XdiFM877Pp0/edit#gid=364842308)
+
+
+# Example Cards:
+
+Below you will find some example cards that this model is capable of outputting.
+You can acquire the images used here: [HF](https://huggingface.co/Dunkindont/Foto-Assisted-Diffusion-FAD_V0/tree/main/Model%20Examples) or
+[Google Drive](https://docs.google.com/spreadsheets/d/1RGRLZhgiFtLMm5Pg8qK0YMc6wr6uvj9-XdiFM877Pp0/edit#gid=364842308). 
+
+Google Drive gives you them all at once without needing to clone the repo, which is easier. 
+
+If you decide to clone it, set ``` GIT_LFS_SKIP_SMUDGE=1 ``` to skip downloading large files
+
+Place them into an EXIF viewer such as the built in "PNG Info" tab in the popular Auto1111 repository to quickly copy the parameters and replicate them!		
+ ## 768x768 Food
+<img src="https://huggingface.co/Dunkindont/Foto-Assisted-Diffusion-FAD_V0/resolve/main/768x768%20Food.jpg" style="max-width: 800px;" width="100%"/>
+
+
+## 768x768 Landscapes
+<img src="https://huggingface.co/Dunkindont/Foto-Assisted-Diffusion-FAD_V0/resolve/main/768x768%20Landscapes.jpg" style="max-width: 800px;" width="100%"/>
+
+## 768x768 People
+<img src="https://huggingface.co/Dunkindont/Foto-Assisted-Diffusion-FAD_V0/resolve/main/768x768%20People.jpg" style="max-width: 800px;" width="100%"/>
+
+## 768x768 Random
+<img src="https://huggingface.co/Dunkindont/Foto-Assisted-Diffusion-FAD_V0/resolve/main/768x768%20Random.jpg" style="max-width: 800px;" width="100%"/>
+
+## 512x512 Artwork
+<img src="https://huggingface.co/Dunkindont/Foto-Assisted-Diffusion-FAD_V0/resolve/main/512x512%20Artwork.jpg" style="max-width: 800px;" width="100%"/>
+
+## 512x512 Photos
+<img src="https://huggingface.co/Dunkindont/Foto-Assisted-Diffusion-FAD_V0/resolve/main/512x512%20Photo.jpg" style="max-width: 800px;" width="100%"/>
+
+## Cloud Support
+Sinkin kindly hosted our model. [Click here to run it on the cloud](https://sinkin.ai/m/V6vYoaL)!
+
+## License
+*My motivation for making this model was to have a free, non-restricted model for the community to use and for startups.*
+
+*I was noticing the models people gravitated towards, were merged models which had prior license requirements from the people who trained them.*
+
+*This was just a fun project I put together for you guys.* 
+
+*My fun ended when I posted the results :D*
+
+*Enjoy! Sharing is caring :)*

feature_extractor/preprocessor_config.json

@@ -0,0 +1,28 @@
+{
+  "crop_size": {
+    "height": 224,
+    "width": 224
+  },
+  "do_center_crop": true,
+  "do_convert_rgb": true,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "feature_extractor_type": "CLIPFeatureExtractor",
+  "image_mean": [
+    0.48145466,
+    0.4578275,
+    0.40821073
+  ],
+  "image_processor_type": "CLIPImageProcessor",
+  "image_std": [
+    0.26862954,
+    0.26130258,
+    0.27577711
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}

license.md

@@ -0,0 +1,3 @@
+License: The CreativeML OpenRAIL M license is an Open RAIL M license, adapted from the work that BigScience and the RAIL Initiative are jointly carrying in the area of responsible AI licensing. See also the article about the BLOOM Open RAIL license on which our license is based.
+
+https://huggingface.co/runwayml/stable-diffusion-v1-5/blob/main/README.md

model_index.json

@@ -0,0 +1,33 @@
+{
+  "_class_name": "StableDiffusionPipeline",
+  "_diffusers_version": "0.10.2",
+  "feature_extractor": [
+    "transformers",
+    "CLIPImageProcessor"
+  ],
+  "requires_safety_checker": true,
+  "safety_checker": [
+    "stable_diffusion",
+    "StableDiffusionSafetyChecker"
+  ],
+  "scheduler": [
+    "diffusers",
+    "DDIMScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "unet": [
+    "diffusers",
+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

safety_checker/config.json

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+{
+  "_commit_hash": "cb41f3a270d63d454d385fc2e4f571c487c253c5",
+  "_name_or_path": "CompVis/stable-diffusion-safety-checker",
+  "architectures": [
+    "StableDiffusionSafetyChecker"
+  ],
+  "initializer_factor": 1.0,
+  "logit_scale_init_value": 2.6592,
+  "model_type": "clip",
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+      "1": "LABEL_1"
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+}

safety_checker/pytorch_model.bin

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+size 1216061799

scheduler/scheduler_config.json

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+{
+  "_class_name": "DDIMScheduler",
+  "_diffusers_version": "0.10.2",
+  "beta_end": 0.012,
+  "beta_schedule": "scaled_linear",
+  "beta_start": 0.00085,
+  "clip_sample": false,
+  "num_train_timesteps": 1000,
+  "prediction_type": "epsilon",
+  "set_alpha_to_one": false,
+  "steps_offset": 1,
+  "trained_betas": null
+}

text_encoder/config.json

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+{
+  "_name_or_path": "openai/clip-vit-large-patch14",
+  "architectures": [
+    "CLIPTextModel"
+  ],
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+  "model_type": "clip_text_model",
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+  "pad_token_id": 1,
+  "projection_dim": 768,
+  "torch_dtype": "float32",
+  "transformers_version": "4.25.1",
+  "vocab_size": 49408
+}

text_encoder/pytorch_model.bin

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tokenizer/special_tokens_map.json

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+{
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+    "normalized": true,
+    "rstrip": false,
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+}

tokenizer/tokenizer_config.json

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+  "name_or_path": "openai/clip-vit-large-patch14",
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+}

unet/config.json

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+{
+  "_class_name": "UNet2DConditionModel",
+  "_diffusers_version": "0.10.2",
+  "act_fn": "silu",
+  "attention_head_dim": 8,
+  "block_out_channels": [
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+    640,
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+  ],
+  "center_input_sample": false,
+  "cross_attention_dim": 768,
+  "down_block_types": [
+    "CrossAttnDownBlock2D",
+    "CrossAttnDownBlock2D",
+    "CrossAttnDownBlock2D",
+    "DownBlock2D"
+  ],
+  "downsample_padding": 1,
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+  "flip_sin_to_cos": true,
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+  "up_block_types": [
+    "UpBlock2D",
+    "CrossAttnUpBlock2D",
+    "CrossAttnUpBlock2D",
+    "CrossAttnUpBlock2D"
+  ],
+  "upcast_attention": false,
+  "use_linear_projection": false
+}

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vae/config.json

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+{
+  "_class_name": "AutoencoderKL",
+  "_diffusers_version": "0.10.2",
+  "act_fn": "silu",
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+    512,
+    512
+  ],
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+    "DownEncoderBlock2D",
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+    "DownEncoderBlock2D",
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+  "up_block_types": [
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+    "UpDecoderBlock2D",
+    "UpDecoderBlock2D",
+    "UpDecoderBlock2D"
+  ]
+}

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