Add Diffusers weights

.gitattributes

@@ -32,4 +32,3 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
-*.png filter=lfs diff=lfs merge=lfs -text

README.md

@@ -7,35 +7,23 @@ language:
 - en
 library_name: diffusers
 ---
-# Banano Chan - Protogen v2.2 (banchan-protogen-v22) V2
+# Banano Chan - Protogen v2.2 (banchan-protogen-v22)
 
 
 A potassium rich latent diffusion model. [Protogen v2.2 (Anime)](https://huggingface.co/darkstorm2150/Protogen_v2.2_Official_Release) trained to the likeness of [Banano Chan](https://twitter.com/Banano_Chan/). The digital waifu embodiment of [Banano](https://www.banano.cc), a feeless and super fast meme cryptocurrency.
 
 This model is intended to produce high-quality, highly detailed images from rich and complex prompts.
 
-```
-Prompt: banchan, 1girl
-Negative prompt: ((disfigured)), ((bad art)), ((deformed)),((extra limbs)), ((bad anatomy)), (((bad proportions)))
-Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 3207496684, Size: 
-768x768, Model hash: 220c1c8ec5, Model: banchanProtogenV2, Clip skip: 2
-```
-
-Share your pictures in the [#banano-ai-art Discord channel](https://discord.com/channels/415935345075421194/991823100054355998) or [Community](https://huggingface.co/Banano/banchan-protogen-v22/discussions) tab.
+eg. `(extremely detailed CG unity 8k wallpaper), green eyes, (green hair_0.8), (yellow hair_0.7), (gradient hair_0.4), full shot body photo of banchan, **<insert an action or a place to here, like bowl of sushi, or riding a jetski)>**. nostalgia professional majestic oil painting by Ed Blinkey, Atey Ghailan, Studio Ghibli, by Jeremy Mann, Greg Manchess, Antonio Moro, trending on ArtStation, trending on CGSociety, Intricate, High Detail, Sharp focus, dramatic, photorealistic painting art by midjourney and greg rutkowski, (((masterpiece))), (((best quality)))`
 
 Test the concept via A1111 Colab [fast-Colab-A1111](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb)
-Or you can run your new concept via `diffusers` [Colab Notebook for Inference](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_dreambooth_inference.ipynb)
-
-Sample pictures:
-![0](./sample_images/00147-393566544.png)
-![1](./sample_images/00027-3207496684.png)
-![2](./sample_images/00026-3428198346.png)
-![3](./sample_images/00031-290723165.png)
-![4](./sample_images/00182-924148568.png)
+
 --
       
 Dreambooth model trained with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook.
 
+
+
 ## License
 
 This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage.

banchan-protogen-v22.ckpt

@@ -1,3 +1,3 @@
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-size 2132868592
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+size 2132866326

banchan-protogen-v22.safetensors

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model_index.json

@@ -1,6 +1,6 @@
 {
   "_class_name": "StableDiffusionPipeline",
-  "_diffusers_version": "0.14.0.dev0",
+  "_diffusers_version": "0.12.0.dev0",
   "feature_extractor": [
     "transformers",
     "CLIPFeatureExtractor"

safety_checker/config.json

@@ -21,6 +21,7 @@
     "decoder_start_token_id": null,
     "diversity_penalty": 0.0,
     "do_sample": false,
+    "dropout": 0.0,
     "early_stopping": false,
     "encoder_no_repeat_ngram_size": 0,
     "eos_token_id": 2,
@@ -79,7 +80,7 @@
     "top_p": 1.0,
     "torch_dtype": null,
     "torchscript": false,
-    "transformers_version": "4.27.0.dev0",
+    "transformers_version": "4.26.0.dev0",
     "typical_p": 1.0,
     "use_bfloat16": false,
     "vocab_size": 49408
@@ -105,6 +106,7 @@
     "decoder_start_token_id": null,
     "diversity_penalty": 0.0,
     "do_sample": false,
+    "dropout": 0.0,
     "early_stopping": false,
     "encoder_no_repeat_ngram_size": 0,
     "eos_token_id": null,
@@ -165,7 +167,7 @@
     "top_p": 1.0,
     "torch_dtype": null,
     "torchscript": false,
-    "transformers_version": "4.27.0.dev0",
+    "transformers_version": "4.26.0.dev0",
     "typical_p": 1.0,
     "use_bfloat16": false
   },

scheduler/scheduler_config.json

@@ -1,6 +1,6 @@
 {
   "_class_name": "PNDMScheduler",
-  "_diffusers_version": "0.14.0.dev0",
+  "_diffusers_version": "0.12.0.dev0",
   "beta_end": 0.012,
   "beta_schedule": "scaled_linear",
   "beta_start": 0.00085,

text_encoder/config.json

@@ -20,6 +20,6 @@
   "pad_token_id": 1,
   "projection_dim": 768,
   "torch_dtype": "float32",
-  "transformers_version": "4.27.0.dev0",
+  "transformers_version": "4.26.0.dev0",
   "vocab_size": 49408
 }

text_encoder/pytorch_model.bin

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 size 492307041

tokenizer/tokenizer_config.json

@@ -19,6 +19,7 @@
   },
   "errors": "replace",
   "model_max_length": 77,
+  "name_or_path": "openai/clip-vit-large-patch14",
   "pad_token": "<|endoftext|>",
   "special_tokens_map_file": "./special_tokens_map.json",
   "tokenizer_class": "CLIPTokenizer",

unet/config.json

@@ -1,6 +1,6 @@
 {
   "_class_name": "UNet2DConditionModel",
-  "_diffusers_version": "0.14.0.dev0",
+  "_diffusers_version": "0.12.0.dev0",
   "act_fn": "silu",
   "attention_head_dim": 8,
   "block_out_channels": [
@@ -11,8 +11,6 @@
   ],
   "center_input_sample": false,
   "class_embed_type": null,
-  "conv_in_kernel": 3,
-  "conv_out_kernel": 3,
   "cross_attention_dim": 768,
   "down_block_types": [
     "CrossAttnDownBlock2D",
@@ -33,12 +31,8 @@
   "num_class_embeds": null,
   "only_cross_attention": false,
   "out_channels": 4,
-  "projection_class_embeddings_input_dim": null,
   "resnet_time_scale_shift": "default",
   "sample_size": 64,
-  "time_cond_proj_dim": null,
-  "time_embedding_type": "positional",
-  "timestep_post_act": null,
   "up_block_types": [
     "UpBlock2D",
     "CrossAttnUpBlock2D",

unet/diffusion_pytorch_model.bin

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 size 3438366373

vae/config.json

@@ -1,6 +1,6 @@
 {
   "_class_name": "AutoencoderKL",
-  "_diffusers_version": "0.14.0.dev0",
+  "_diffusers_version": "0.12.0.dev0",
   "act_fn": "silu",
   "block_out_channels": [
     128,
@@ -20,7 +20,6 @@
   "norm_num_groups": 32,
   "out_channels": 3,
   "sample_size": 512,
-  "scaling_factor": 0.18215,
   "up_block_types": [
     "UpDecoderBlock2D",
     "UpDecoderBlock2D",