upload model.

README.md

@@ -1,10 +1,10 @@
 ---
-title: Test
-emoji: 🐠
-colorFrom: green
-colorTo: purple
+title: Discoo Diffusion
+emoji: 📚
+colorFrom: pink
+colorTo: blue
 sdk: gradio
-sdk_version: 3.11.0
+sdk_version: 3.10.1
 app_file: app.py
 pinned: false
 license: apache-2.0

app.py

@@ -0,0 +1,32 @@
+import os
+import gradio as gr
+import PIL.Image
+import numpy as np
+import random
+import torch
+import subprocess
+from diffusers import StableDiffusionPipeline
+
+model_id = "dicoo_model"
+
+pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float)
+
+def predict(prompt, steps=50, seed=42, guidance_scale=7.5):
+    print("prompt:", prompt)
+    image = pipe(prompt, num_inference_steps=steps, guidance_scale=7.5).images[0]
+    return image
+
+random_seed = random.randint(0, 2147483647)
+gr.Interface(
+    predict,
+    inputs=[
+        gr.inputs.Textbox(label='Prompt', default='a lovely <dicoo> in red dress and hat, in the snowy and brightly night, with many brightly buildings'),
+        gr.inputs.Slider(1, 100, label='Inference Steps', default=50, step=1),
+        gr.inputs.Slider(0, 2147483647, label='Seed', default=random_seed, step=1),
+        gr.inputs.Slider(1.0, 20.0, label='Guidance Scale - how much the prompt will influence the results', default=6.0, step=0.1),
+    ],
+    outputs=gr.Image(shape=[512, 512], type="pil", elem_id="output_image"),
+    css="#output_image{width: 256px}",
+    title="Demo of dicoo-finetuned-diffusion-model using Intel Neural Compressor 🧨",
+    description="This Spaces app is same as <a href=\"https://huggingface.co/spaces/Intel/dicoo_diffusion\">Intel/dicoo_diffusion</a>, created by Intel AIA/AIPC team with the model fine-tuned with one shot (one image) for a newly introduced object \"dicoo\". To replicate the model fine-tuning, please refer to the code sample in <a href=\"https://github.com/intel/neural-compressor/tree/master/examples/pytorch/diffusion_model/diffusers/textual_inversion\">Intel Neural Compressor</a>. You may also refer to our <a href=\"https://medium.com/intel-analytics-software/personalized-stable-diffusion-with-few-shot-fine-tuning-on-a-single-cpu-f01a3316b13\">blog</a> for more details.",
+).launch()

dicoo_model/feature_extractor/preprocessor_config.json

@@ -0,0 +1,20 @@
+{
+  "crop_size": 224,
+  "do_center_crop": true,
+  "do_convert_rgb": true,
+  "do_normalize": true,
+  "do_resize": true,
+  "feature_extractor_type": "CLIPFeatureExtractor",
+  "image_mean": [
+    0.48145466,
+    0.4578275,
+    0.40821073
+  ],
+  "image_std": [
+    0.26862954,
+    0.26130258,
+    0.27577711
+  ],
+  "resample": 3,
+  "size": 224
+}

dicoo_model/learned_embeds.bin

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dicoo_model/logs/textual_inversion/1668778020.7387893/events.out.tfevents.1668778020.skyocean.3819933.1

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dicoo_model/logs/textual_inversion/1668778020.739862/hparams.yml

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+adam_beta1: 0.9
+adam_beta2: 0.999
+adam_epsilon: 1.0e-08
+adam_weight_decay: 0.01
+center_crop: false
+gradient_accumulation_steps: 1
+hub_model_id: null
+hub_token: null
+initializer_token: toy
+learnable_property: object
+learning_rate: 0.002
+local_rank: -1
+logging_dir: logs
+lr_scheduler: constant
+lr_warmup_steps: 0
+max_train_steps: 3000
+mixed_precision: 'no'
+num_train_epochs: 24
+output_dir: dicoo2_model
+placeholder_token: <dicoo>
+pretrained_model_name_or_path: ../text_to_image/stable-diffusion-v1-4
+push_to_hub: false
+repeats: 100
+resolution: 512
+save_steps: 500
+scale_lr: true
+seed: null
+tokenizer_name: null
+train_batch_size: 4
+train_data_dir: dicoo2/concept_images/

dicoo_model/logs/textual_inversion/events.out.tfevents.1668778020.skyocean.3819933.0

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dicoo_model/model_index.json

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+{
+  "_class_name": "StableDiffusionPipeline",
+  "_diffusers_version": "0.4.1",
+  "feature_extractor": [
+    "transformers",
+    "CLIPFeatureExtractor"
+  ],
+  "safety_checker": [
+    "stable_diffusion",
+    "StableDiffusionSafetyChecker"
+  ],
+  "scheduler": [
+    "diffusers",
+    "PNDMScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "unet": [
+    "diffusers",
+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

dicoo_model/safety_checker/config.json

@@ -0,0 +1,174 @@
+{
+  "_name_or_path": "CompVis/stable-diffusion-safety-checker",
+  "architectures": [
+    "StableDiffusionSafetyChecker"
+  ],
+  "initializer_factor": 1.0,
+  "logit_scale_init_value": 2.6592,
+  "model_type": "clip",
+  "projection_dim": 768,
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+    "hidden_act": "quick_gelu",
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+    "id2label": {
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+      "1": "LABEL_1"
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+    "model_type": "clip_text_model",
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+    "num_attention_heads": 12,
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+    "id2label": {
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+      "1": "LABEL_1"
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+}

dicoo_model/safety_checker/pytorch_model.bin

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dicoo_model/scheduler/scheduler_config.json

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+{
+  "_class_name": "PNDMScheduler",
+  "_diffusers_version": "0.4.1",
+  "beta_end": 0.012,
+  "beta_schedule": "scaled_linear",
+  "beta_start": 0.00085,
+  "num_train_timesteps": 1000,
+  "set_alpha_to_one": false,
+  "skip_prk_steps": true,
+  "steps_offset": 1,
+  "trained_betas": null
+}

dicoo_model/text_encoder/config.json

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+{
+  "_name_or_path": "../text_to_image/stable-diffusion-v1-4",
+  "architectures": [
+    "CLIPTextModel"
+  ],
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+  "torch_dtype": "float32",
+  "transformers_version": "4.21.2",
+  "vocab_size": 49409
+}

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dicoo_model/tokenizer/added_tokens.json

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+{
+  "<dicoo>": 49408
+}

dicoo_model/tokenizer/special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<|startoftext|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
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+  }
+}

dicoo_model/tokenizer/tokenizer_config.json

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+{
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+  "model_max_length": 77,
+  "name_or_path": "../text_to_image/stable-diffusion-v1-4",
+  "pad_token": "<|endoftext|>",
+  "special_tokens_map_file": "./special_tokens_map.json",
+  "tokenizer_class": "CLIPTokenizer",
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+    "__type": "AddedToken",
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}

dicoo_model/unet/config.json

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+{
+  "_class_name": "UNet2DConditionModel",
+  "_diffusers_version": "0.4.1",
+  "_name_or_path": "../text_to_image/stable-diffusion-v1-4",
+  "act_fn": "silu",
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+  "down_block_types": [
+    "CrossAttnDownBlock2D",
+    "CrossAttnDownBlock2D",
+    "CrossAttnDownBlock2D",
+    "DownBlock2D"
+  ],
+  "downsample_padding": 1,
+  "flip_sin_to_cos": true,
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+  "in_channels": 4,
+  "layers_per_block": 2,
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+  "out_channels": 4,
+  "sample_size": 64,
+  "up_block_types": [
+    "UpBlock2D",
+    "CrossAttnUpBlock2D",
+    "CrossAttnUpBlock2D",
+    "CrossAttnUpBlock2D"
+  ]
+}

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dicoo_model/vae/config.json

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+  "_class_name": "AutoencoderKL",
+  "_diffusers_version": "0.4.1",
+  "_name_or_path": "../text_to_image/stable-diffusion-v1-4",
+  "act_fn": "silu",
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+  "up_block_types": [
+    "UpDecoderBlock2D",
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+    "UpDecoderBlock2D",
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+  ]
+}

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requirements.txt

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+torch
+diffusers==0.4.1
+transformers==4.21.2