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FLUX.1-dev-bnb-8bit/README.md

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+---
+base_model: black-forest-labs/FLUX.1-dev
+library_name: diffusers
+base_model_relation: quantized
+tags:
+- quantization
+---
+
+# Visual comparison of Flux-dev model outputs using BF16 and BnB 8-bit quantization
+
+<td style="text-align: center;">
+  BF16<br>
+  <medium-zoom background="rgba(0,0,0,.7)"><img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/quantization-backends-diffusers/combined_flux-dev_bf16_combined.png" alt="Flux-dev output with BF16: Baroque, Futurist, Noir styles"></medium-zoom>
+</td>
+<td style="text-align: center;">
+  BnB 8-bit<br>
+  <medium-zoom background="rgba(0,0,0,.7)"><img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/quantization-backends-diffusers/combined_flux-dev_bnb_8bit_combined.png" alt="Flux-dev output with BnB 8-bit: Baroque, Futurist, Noir styles"></medium-zoom>
+</td>
+
+# Usage with Diffusers
+
+To use this quantized FLUX.1 [dev] checkpoint, you need to install the 🧨 diffusers and bitsandbytes library:
+
+```
+pip install -U diffusers
+pip install -U bitsandbytes
+```
+
+After installing the required library, you can run the following script: 
+
+```python
+from diffusers import FluxPipeline
+
+pipe = FluxPipeline.from_pretrained(
+    "diffusers/FLUX.1-dev-bnb-8bit",
+    torch_dtype=torch.bfloat16
+)
+pipe.to("cuda")
+
+prompt = "Baroque style, a lavish palace interior with ornate gilded ceilings, intricate tapestries, and dramatic lighting over a grand staircase."
+
+pipe_kwargs = {
+    "prompt": prompt,
+    "height": 1024,
+    "width": 1024,
+    "guidance_scale": 3.5,
+    "num_inference_steps": 50,
+    "max_sequence_length": 512,
+}
+
+image = pipe(
+    **pipe_kwargs, generator=torch.manual_seed(0),
+).images[0]
+
+image.save("flux.png")
+```
+
+# How to generate this quantized checkpoint ? 
+
+This checkpoint was created with the following script using "black-forest-labs/FLUX.1-dev" checkpoint:
+
+```python
+
+import torch
+from diffusers import FluxPipeline
+from diffusers import BitsAndBytesConfig as DiffusersBitsAndBytesConfig
+from diffusers.quantizers import PipelineQuantizationConfig
+from transformers import BitsAndBytesConfig as TransformersBitsAndBytesConfig
+
+pipeline_quant_config = PipelineQuantizationConfig(
+    quant_mapping={
+        "transformer": DiffusersBitsAndBytesConfig(load_in_8bit=True),
+        "text_encoder_2": TransformersBitsAndBytesConfig(load_in_8bit=True),
+    }
+)
+
+pipe = FluxPipeline.from_pretrained(
+    "black-forest-labs/FLUX.1-dev",
+    quantization_config=pipeline_quant_config,
+    torch_dtype=torch.bfloat16
+)
+
+pipe.save_pretrained("FLUX.1-dev-bnb-8bit")
+```

FLUX.1-dev-bnb-8bit/model_index.json

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+{
+  "_class_name": "FluxPipeline",
+  "_diffusers_version": "0.34.0.dev0",
+  "_name_or_path": "black-forest-labs/FLUX.1-dev",
+  "feature_extractor": [
+    null,
+    null
+  ],
+  "image_encoder": [
+    null,
+    null
+  ],
+  "scheduler": [
+    "diffusers",
+    "FlowMatchEulerDiscreteScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "text_encoder_2": [
+    "transformers",
+    "T5EncoderModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "tokenizer_2": [
+    "transformers",
+    "T5TokenizerFast"
+  ],
+  "transformer": [
+    "diffusers",
+    "FluxTransformer2DModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

FLUX.1-dev-bnb-8bit/scheduler/scheduler_config.json

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+{
+  "_class_name": "FlowMatchEulerDiscreteScheduler",
+  "_diffusers_version": "0.34.0.dev0",
+  "base_image_seq_len": 256,
+  "base_shift": 0.5,
+  "invert_sigmas": false,
+  "max_image_seq_len": 4096,
+  "max_shift": 1.15,
+  "num_train_timesteps": 1000,
+  "shift": 3.0,
+  "shift_terminal": null,
+  "stochastic_sampling": false,
+  "time_shift_type": "exponential",
+  "use_beta_sigmas": false,
+  "use_dynamic_shifting": true,
+  "use_exponential_sigmas": false,
+  "use_karras_sigmas": false
+}

FLUX.1-dev-bnb-8bit/text_encoder/config.json

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+{
+  "architectures": [
+    "CLIPTextModel"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 0,
+  "dropout": 0.0,
+  "eos_token_id": 2,
+  "hidden_act": "quick_gelu",
+  "hidden_size": 768,
+  "initializer_factor": 1.0,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 77,
+  "model_type": "clip_text_model",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "projection_dim": 768,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.52.0.dev0",
+  "vocab_size": 49408
+}

FLUX.1-dev-bnb-8bit/text_encoder_2/config.json

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+{
+  "architectures": [
+    "T5EncoderModel"
+  ],
+  "classifier_dropout": 0.0,
+  "d_ff": 10240,
+  "d_kv": 64,
+  "d_model": 4096,
+  "decoder_start_token_id": 0,
+  "dense_act_fn": "gelu_new",
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "gated-gelu",
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "is_gated_act": true,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "t5",
+  "num_decoder_layers": 24,
+  "num_heads": 64,
+  "num_layers": 24,
+  "output_past": true,
+  "pad_token_id": 0,
+  "quantization_config": {
+    "_load_in_4bit": false,
+    "_load_in_8bit": true,
+    "bnb_4bit_compute_dtype": "float32",
+    "bnb_4bit_quant_storage": "uint8",
+    "bnb_4bit_quant_type": "fp4",
+    "bnb_4bit_use_double_quant": false,
+    "llm_int8_enable_fp32_cpu_offload": false,
+    "llm_int8_has_fp16_weight": false,
+    "llm_int8_skip_modules": null,
+    "llm_int8_threshold": 6.0,
+    "load_in_4bit": false,
+    "load_in_8bit": true,
+    "quant_method": "bitsandbytes"
+  },
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.52.0.dev0",
+  "use_cache": true,
+  "vocab_size": 32128
+}

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FLUX.1-dev-bnb-8bit/tokenizer/special_tokens_map.json

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+}

FLUX.1-dev-bnb-8bit/tokenizer/tokenizer_config.json

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FLUX.1-dev-bnb-8bit/tokenizer_2/special_tokens_map.json

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+    "<extra_id_18>",
+    "<extra_id_19>",
+    "<extra_id_20>",
+    "<extra_id_21>",
+    "<extra_id_22>",
+    "<extra_id_23>",
+    "<extra_id_24>",
+    "<extra_id_25>",
+    "<extra_id_26>",
+    "<extra_id_27>",
+    "<extra_id_28>",
+    "<extra_id_29>",
+    "<extra_id_30>",
+    "<extra_id_31>",
+    "<extra_id_32>",
+    "<extra_id_33>",
+    "<extra_id_34>",
+    "<extra_id_35>",
+    "<extra_id_36>",
+    "<extra_id_37>",
+    "<extra_id_38>",
+    "<extra_id_39>",
+    "<extra_id_40>",
+    "<extra_id_41>",
+    "<extra_id_42>",
+    "<extra_id_43>",
+    "<extra_id_44>",
+    "<extra_id_45>",
+    "<extra_id_46>",
+    "<extra_id_47>",
+    "<extra_id_48>",
+    "<extra_id_49>",
+    "<extra_id_50>",
+    "<extra_id_51>",
+    "<extra_id_52>",
+    "<extra_id_53>",
+    "<extra_id_54>",
+    "<extra_id_55>",
+    "<extra_id_56>",
+    "<extra_id_57>",
+    "<extra_id_58>",
+    "<extra_id_59>",
+    "<extra_id_60>",
+    "<extra_id_61>",
+    "<extra_id_62>",
+    "<extra_id_63>",
+    "<extra_id_64>",
+    "<extra_id_65>",
+    "<extra_id_66>",
+    "<extra_id_67>",
+    "<extra_id_68>",
+    "<extra_id_69>",
+    "<extra_id_70>",
+    "<extra_id_71>",
+    "<extra_id_72>",
+    "<extra_id_73>",
+    "<extra_id_74>",
+    "<extra_id_75>",
+    "<extra_id_76>",
+    "<extra_id_77>",
+    "<extra_id_78>",
+    "<extra_id_79>",
+    "<extra_id_80>",
+    "<extra_id_81>",
+    "<extra_id_82>",
+    "<extra_id_83>",
+    "<extra_id_84>",
+    "<extra_id_85>",
+    "<extra_id_86>",
+    "<extra_id_87>",
+    "<extra_id_88>",
+    "<extra_id_89>",
+    "<extra_id_90>",
+    "<extra_id_91>",
+    "<extra_id_92>",
+    "<extra_id_93>",
+    "<extra_id_94>",
+    "<extra_id_95>",
+    "<extra_id_96>",
+    "<extra_id_97>",
+    "<extra_id_98>",
+    "<extra_id_99>"
+  ],
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

FLUX.1-dev-bnb-8bit/tokenizer_2/tokenizer_config.json

@@ -0,0 +1,941 @@
+{
+  "add_prefix_space": true,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32000": {
+      "content": "<extra_id_99>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32001": {
+      "content": "<extra_id_98>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32002": {
+      "content": "<extra_id_97>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32003": {
+      "content": "<extra_id_96>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32004": {
+      "content": "<extra_id_95>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32005": {
+      "content": "<extra_id_94>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32006": {
+      "content": "<extra_id_93>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32007": {
+      "content": "<extra_id_92>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32008": {
+      "content": "<extra_id_91>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32009": {
+      "content": "<extra_id_90>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32010": {
+      "content": "<extra_id_89>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32011": {
+      "content": "<extra_id_88>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32012": {
+      "content": "<extra_id_87>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32013": {
+      "content": "<extra_id_86>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32014": {
+      "content": "<extra_id_85>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32015": {
+      "content": "<extra_id_84>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32016": {
+      "content": "<extra_id_83>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32017": {
+      "content": "<extra_id_82>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32018": {
+      "content": "<extra_id_81>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32019": {
+      "content": "<extra_id_80>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32020": {
+      "content": "<extra_id_79>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32021": {
+      "content": "<extra_id_78>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32022": {
+      "content": "<extra_id_77>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32023": {
+      "content": "<extra_id_76>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32024": {
+      "content": "<extra_id_75>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32025": {
+      "content": "<extra_id_74>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32026": {
+      "content": "<extra_id_73>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32027": {
+      "content": "<extra_id_72>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32028": {
+      "content": "<extra_id_71>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32029": {
+      "content": "<extra_id_70>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32030": {
+      "content": "<extra_id_69>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32031": {
+      "content": "<extra_id_68>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32032": {
+      "content": "<extra_id_67>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32033": {
+      "content": "<extra_id_66>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32034": {
+      "content": "<extra_id_65>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32035": {
+      "content": "<extra_id_64>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32036": {
+      "content": "<extra_id_63>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32037": {
+      "content": "<extra_id_62>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32038": {
+      "content": "<extra_id_61>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32039": {
+      "content": "<extra_id_60>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32040": {
+      "content": "<extra_id_59>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32041": {
+      "content": "<extra_id_58>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32042": {
+      "content": "<extra_id_57>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32043": {
+      "content": "<extra_id_56>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32044": {
+      "content": "<extra_id_55>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32045": {
+      "content": "<extra_id_54>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32046": {
+      "content": "<extra_id_53>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32047": {
+      "content": "<extra_id_52>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32048": {
+      "content": "<extra_id_51>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32049": {
+      "content": "<extra_id_50>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32050": {
+      "content": "<extra_id_49>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32051": {
+      "content": "<extra_id_48>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32052": {
+      "content": "<extra_id_47>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32053": {
+      "content": "<extra_id_46>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32054": {
+      "content": "<extra_id_45>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32055": {
+      "content": "<extra_id_44>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32056": {
+      "content": "<extra_id_43>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32057": {
+      "content": "<extra_id_42>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32058": {
+      "content": "<extra_id_41>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32059": {
+      "content": "<extra_id_40>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32060": {
+      "content": "<extra_id_39>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32061": {
+      "content": "<extra_id_38>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32062": {
+      "content": "<extra_id_37>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32063": {
+      "content": "<extra_id_36>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32064": {
+      "content": "<extra_id_35>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32065": {
+      "content": "<extra_id_34>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32066": {
+      "content": "<extra_id_33>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32067": {
+      "content": "<extra_id_32>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32068": {
+      "content": "<extra_id_31>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32069": {
+      "content": "<extra_id_30>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32070": {
+      "content": "<extra_id_29>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32071": {
+      "content": "<extra_id_28>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32072": {
+      "content": "<extra_id_27>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32073": {
+      "content": "<extra_id_26>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32074": {
+      "content": "<extra_id_25>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32075": {
+      "content": "<extra_id_24>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32076": {
+      "content": "<extra_id_23>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32077": {
+      "content": "<extra_id_22>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32078": {
+      "content": "<extra_id_21>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32079": {
+      "content": "<extra_id_20>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32080": {
+      "content": "<extra_id_19>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32081": {
+      "content": "<extra_id_18>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32082": {
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+      "lstrip": false,
+      "normalized": false,
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+    },
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+      "lstrip": false,
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+    },
+    "32084": {
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+      "lstrip": false,
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+    },
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+      "lstrip": false,
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+      "special": true
+    },
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+      "lstrip": false,
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+      "special": true
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+  "unk_token": "<unk>"
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FLUX.1-dev-bnb-8bit/transformer/config.json

@@ -0,0 +1,35 @@
+{
+  "_class_name": "FluxTransformer2DModel",
+  "_diffusers_version": "0.34.0.dev0",
+  "_name_or_path": "/raid/marc/models--black-forest-labs--FLUX.1-dev/snapshots/0ef5fff789c832c5c7f4e127f94c8b54bbcced44/transformer",
+  "attention_head_dim": 128,
+  "axes_dims_rope": [
+    16,
+    56,
+    56
+  ],
+  "guidance_embeds": true,
+  "in_channels": 64,
+  "joint_attention_dim": 4096,
+  "num_attention_heads": 24,
+  "num_layers": 19,
+  "num_single_layers": 38,
+  "out_channels": null,
+  "patch_size": 1,
+  "pooled_projection_dim": 768,
+  "quantization_config": {
+    "_load_in_4bit": false,
+    "_load_in_8bit": true,
+    "bnb_4bit_compute_dtype": "float32",
+    "bnb_4bit_quant_storage": "uint8",
+    "bnb_4bit_quant_type": "fp4",
+    "bnb_4bit_use_double_quant": false,
+    "llm_int8_enable_fp32_cpu_offload": false,
+    "llm_int8_has_fp16_weight": false,
+    "llm_int8_skip_modules": null,
+    "llm_int8_threshold": 6.0,
+    "load_in_4bit": false,
+    "load_in_8bit": true,
+    "quant_method": "bitsandbytes"
+  }
+}

FLUX.1-dev-bnb-8bit/vae/config.json

@@ -0,0 +1,38 @@
+{
+  "_class_name": "AutoencoderKL",
+  "_diffusers_version": "0.34.0.dev0",
+  "_name_or_path": "/raid/marc/models--black-forest-labs--FLUX.1-dev/snapshots/0ef5fff789c832c5c7f4e127f94c8b54bbcced44/vae",
+  "act_fn": "silu",
+  "block_out_channels": [
+    128,
+    256,
+    512,
+    512
+  ],
+  "down_block_types": [
+    "DownEncoderBlock2D",
+    "DownEncoderBlock2D",
+    "DownEncoderBlock2D",
+    "DownEncoderBlock2D"
+  ],
+  "force_upcast": true,
+  "in_channels": 3,
+  "latent_channels": 16,
+  "latents_mean": null,
+  "latents_std": null,
+  "layers_per_block": 2,
+  "mid_block_add_attention": true,
+  "norm_num_groups": 32,
+  "out_channels": 3,
+  "sample_size": 1024,
+  "scaling_factor": 0.3611,
+  "shift_factor": 0.1159,
+  "up_block_types": [
+    "UpDecoderBlock2D",
+    "UpDecoderBlock2D",
+    "UpDecoderBlock2D",
+    "UpDecoderBlock2D"
+  ],
+  "use_post_quant_conv": false,
+  "use_quant_conv": false
+}

Heartsync_NSFW-Uncensored/README.md

@@ -0,0 +1,86 @@
+---
+license: mit
+language:
+- en
+pipeline_tag: text-to-image
+tags:
+- stablediffusion
+- uncensored
+- nsfw
+- image
+- generation
+widget:
+  - text: >-
+      TEST
+    output:
+      url: samples/nsfw1.webp
+  - text: >-
+      TEST
+    output:
+      url: samples/nsfw2.webp
+  - text: >-
+      TEST
+    output:
+      url: samples/nsfw3.webp
+  - text: >-
+      TEST
+    output:
+      url: samples/nsfw4.webp      
+---
+# NSFW-Uncensored
+
+## Uncensored Image Generation Model
+
+#### Model Description
+This model is a playground that minimizes censorship restrictions, allowing exploration of the technical possibilities of AI-based image generation. Through various prompts, you can test censorship boundaries and verify the actual performance of image generation AI.
+
+## Example code
+
+```python
+# Basic usage example
+from diffusers import DiffusionPipeline
+import torch
+
+# Load the model (with float16 precision for GPU)
+pipe = DiffusionPipeline.from_pretrained(
+    "Heartsync/NSFW-Uncensored",
+    torch_dtype=torch.float16
+)
+pipe.to("cuda")  # Move to GPU
+
+# Generate an image with a simple prompt
+prompt = "Woman in an elegant dress standing by a window, detailed lighting, 8k"
+negative_prompt = "low quality, blurry, deformed"
+
+# Create the image
+image = pipe(
+    prompt=prompt,
+    negative_prompt=negative_prompt,
+    num_inference_steps=30,
+    guidance_scale=7.5
+).images[0]
+
+# Save the image
+image.save("generated_image.png")
+
+# Advanced example - fixed seed and additional parameters
+import numpy as np
+
+# Set seed for reproducible results
+seed = 42
+generator = torch.Generator("cuda").manual_seed(seed)
+
+# Advanced parameter settings
+prompt = "A dramatic scene with explicit details, cinematic lighting, high resolution"
+image = pipe(
+    prompt=prompt,
+    negative_prompt="ugly, deformed, disfigured, poor quality, low resolution",
+    num_inference_steps=50,  # More steps for higher quality
+    guidance_scale=8.0,     # Increase prompt fidelity
+    width=768,              # Adjust image width
+    height=768,             # Adjust image height
+    generator=generator     # Fixed seed
+).images[0]
+
+image.save("high_quality_image.png")
+```

Heartsync_NSFW-Uncensored/model_index.json

@@ -0,0 +1,41 @@
+{
+  "_class_name": "StableDiffusionXLPipeline",
+  "_diffusers_version": "0.27.2",
+  "feature_extractor": [
+    null,
+    null
+  ],
+  "force_zeros_for_empty_prompt": true,
+  "image_encoder": [
+    null,
+    null
+  ],
+  "scheduler": [
+    "diffusers",
+    "EulerDiscreteScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "text_encoder_2": [
+    "transformers",
+    "CLIPTextModelWithProjection"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "tokenizer_2": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "unet": [
+    "diffusers",
+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

Heartsync_NSFW-Uncensored/test_app.py

@@ -0,0 +1,46 @@
+# Basic usage example
+from diffusers import DiffusionPipeline
+import torch
+
+# Load the model (with float16 precision for GPU)
+pipe = DiffusionPipeline.from_pretrained(
+    "Heartsync/NSFW-Uncensored",
+    torch_dtype=torch.float16
+)
+pipe.to("cuda")  # Move to GPU
+
+# Generate an image with a simple prompt
+prompt = "Woman in an elegant dress standing by a window, detailed lighting, 8k"
+negative_prompt = "low quality, blurry, deformed"
+
+# Create the image
+image = pipe(
+    prompt=prompt,
+    negative_prompt=negative_prompt,
+    num_inference_steps=30,
+    guidance_scale=7.5
+).images[0]
+
+# Save the image
+image.save("generated_image.png")
+
+# Advanced example - fixed seed and additional parameters
+import numpy as np
+
+# Set seed for reproducible results
+seed = 42
+generator = torch.Generator("cuda").manual_seed(seed)
+
+# Advanced parameter settings
+prompt = "A dramatic scene with explicit details, cinematic lighting, high resolution"
+image = pipe(
+    prompt=prompt,
+    negative_prompt="ugly, deformed, disfigured, poor quality, low resolution",
+    num_inference_steps=50,  # More steps for higher quality
+    guidance_scale=8.0,     # Increase prompt fidelity
+    width=768,              # Adjust image width
+    height=768,             # Adjust image height
+    generator=generator     # Fixed seed
+).images[0]
+
+image.save("high_quality_image.png")

LoliV5-edited/README.md

@@ -0,0 +1,8 @@
+---
+duplicated_from: kebab111/LoliV5
+license: creativeml-openrail-m
+tags:
+  - stable-diffusion
+  - text-to-image
+---
+i have no idea what i am doing

LoliV5-edited/model_index.json

@@ -0,0 +1,33 @@
+{
+  "_class_name": "StableDiffusionPipeline",
+  "_diffusers_version": "0.13.1",
+  "feature_extractor": [
+    "transformers",
+    "CLIPFeatureExtractor"
+  ],
+  "requires_safety_checker": false,
+  "safety_checker": [
+    null,
+    null
+  ],
+  "scheduler": [
+    "diffusers",
+    "PNDMScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "unet": [
+    "diffusers",
+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

Qwen-Image-Edit-2511-bnb-nf4/README.md

@@ -0,0 +1,167 @@
+---
+license: apache-2.0
+library_name: diffusers
+base_model: Qwen/Qwen-Image-Edit-2511
+tags:
+  - image-to-image
+  - image-editing
+  - qwen
+  - quantized
+  - bitsandbytes
+  - nf4
+  - 4bit
+pipeline_tag: image-to-image
+---
+
+# Qwen-Image-Edit-2511-bnb-nf4
+
+4-bit NF4 quantized version of [Qwen-Image-Edit-2511](https://huggingface.co/Qwen/Qwen-Image-Edit-2511) using BitsAndBytes.
+
+This quantized model significantly reduces VRAM requirements, making it accessible on consumer GPUs like RTX 3090/4080/4090.
+
+## Sample Outputs
+
+### Single Image Editing
+
+<table>
+<tr>
+<th>Input</th>
+<th>Prompt</th>
+<th>Output</th>
+</tr>
+<tr>
+<td><img src="samples/inputs/cat.jpg" width="200"></td>
+<td>"A cat wearing stylish sunglasses"</td>
+<td><img src="samples/cat_sunglasses.png" width="200"></td>
+</tr>
+<tr>
+<td><img src="samples/inputs/portrait.jpg" width="200"></td>
+<td>"Cyberpunk style with neon lights"</td>
+<td><img src="samples/portrait_cyberpunk.png" width="200"></td>
+</tr>
+</table>
+
+### Multi-Image Editing
+
+Combine multiple images into one coherent scene:
+
+<table>
+<tr>
+<th>Input 1</th>
+<th>Input 2</th>
+<th>Prompt</th>
+<th>Output</th>
+</tr>
+<tr>
+<td><img src="samples/inputs/cat.jpg" width="150"></td>
+<td><img src="samples/inputs/mountain.jpg" width="150"></td>
+<td>"A cat sitting on a mountain cliff"</td>
+<td><img src="samples/multi_cat_mountain.png" width="200"></td>
+</tr>
+<tr>
+<td><img src="samples/inputs/portrait.jpg" width="150"></td>
+<td><img src="samples/inputs/mountain.jpg" width="150"></td>
+<td>"Person hiking in the mountains"</td>
+<td><img src="samples/multi_portrait_mountain.png" width="200"></td>
+</tr>
+</table>
+
+### Style Transfer
+
+<table>
+<tr>
+<th>Input</th>
+<th>Style</th>
+<th>Output</th>
+</tr>
+<tr>
+<td><img src="samples/inputs/mountain.jpg" width="200"></td>
+<td>Studio Ghibli</td>
+<td><img src="samples/mountain_ghibli.png" width="200"></td>
+</tr>
+<tr>
+<td><img src="samples/inputs/mountain.jpg" width="200"></td>
+<td>Winter + Northern Lights</td>
+<td><img src="samples/mountain_winter.png" width="200"></td>
+</tr>
+</table>
+
+## Features
+
+- **Reduced VRAM**: ~17GB vs ~40GB (original BF16)
+- **Same capabilities**: Single/multi-image editing, style transfer, character consistency
+- **BitsAndBytes NF4**: High-quality 4-bit quantization
+
+## Requirements
+
+```bash
+pip install torch diffusers transformers accelerate bitsandbytes
+```
+
+## Usage
+
+```python
+import torch
+from PIL import Image
+from diffusers import QwenImageEditPlusPipeline
+
+# Load quantized model
+pipe = QwenImageEditPlusPipeline.from_pretrained(
+    "seochan99/Qwen-Image-Edit-2511-bnb-nf4",
+    torch_dtype=torch.bfloat16,
+)
+pipe.to("cuda")
+
+# Single image editing
+image = Image.open("input.png")
+result = pipe(
+    image=[image],
+    prompt="Turn this into anime style",
+    true_cfg_scale=4.0,
+    negative_prompt=" ",
+    num_inference_steps=50,
+).images[0]
+result.save("output.png")
+```
+
+## Multi-Image Editing
+
+Combine two images into one coherent scene:
+
+```python
+img1 = Image.open("person.png")
+img2 = Image.open("background.png")
+
+result = pipe(
+    image=[img1, img2],
+    prompt="Person standing in the forest, natural lighting",
+    true_cfg_scale=4.0,
+    negative_prompt=" ",
+    num_inference_steps=50,
+).images[0]
+```
+
+## VRAM Comparison
+
+| Version | VRAM Usage |
+|---------|------------|
+| Original (BF16) | ~40GB |
+| **This (NF4 4-bit)** | **~17GB** |
+
+Tested on NVIDIA RTX 4090.
+
+## Quantization Details
+
+- **Method**: BitsAndBytes NF4 (4-bit Normal Float)
+- **Compute dtype**: bfloat16
+- **Components quantized**: text_encoder, transformer
+
+## Model Info
+
+- **Base model**: [Qwen/Qwen-Image-Edit-2511](https://huggingface.co/Qwen/Qwen-Image-Edit-2511)
+- **Paper**: [arXiv:2508.02324](https://arxiv.org/abs/2508.02324)
+- **Original repo**: [QwenLM/Qwen-Image](https://github.com/QwenLM/Qwen-Image)
+
+## License
+
+Apache 2.0 (same as base model)

Qwen-Image-Edit-2511-bnb-nf4/model_index.json

@@ -0,0 +1,29 @@
+{
+  "_class_name": "QwenImageEditPlusPipeline",
+  "_diffusers_version": "0.37.0.dev0",
+  "_name_or_path": "Qwen/Qwen-Image-Edit-2511",
+  "processor": [
+    "transformers",
+    "Qwen2VLProcessor"
+  ],
+  "scheduler": [
+    "diffusers",
+    "FlowMatchEulerDiscreteScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "Qwen2_5_VLForConditionalGeneration"
+  ],
+  "tokenizer": [
+    "transformers",
+    "Qwen2Tokenizer"
+  ],
+  "transformer": [
+    "diffusers",
+    "QwenImageTransformer2DModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKLQwenImage"
+  ]
+}

Stable-Diffusion-Pokemon-en/README.md

@@ -0,0 +1,206 @@
+---
+language: en
+license: other
+tags:
+- stable-diffusion
+- stable-diffusion-diffusers
+- text-to-image
+- en
+- english
+inference: false
+extra_gated_prompt: |-
+  One more step before getting this model.
+  This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage.
+  The CreativeML OpenRAIL License specifies: 
+
+  1. You can't use the model to deliberately produce nor share illegal or harmful outputs or content 
+  2. rinna Co., Ltd. claims no rights on the outputs you generate, you are free to use them and are accountable for their use which must not go against the provisions set in the license
+  3. You may re-distribute the weights and use the model commercially and/or as a service. If you do, please be aware you have to include the same use restrictions as the ones in the license and share a copy of the CreativeML OpenRAIL-M to all your users (please read the license entirely and carefully)
+  Please read the full license here: https://huggingface.co/spaces/CompVis/stable-diffusion-license
+  
+  By clicking on "Access repository" below, you accept that your *contact information* (email address and username) can be shared with the model authors as well.
+    
+extra_gated_fields:
+ I have read the License and agree with its terms: checkbox
+---
+
+
+# English Stable Diffusion Pokemon Model Card
+
+<!--
+![rinna](https://github.com/rinnakk/japanese-clip/blob/master/data/rinna.png?raw=true)
+-->
+
+Stable-Diffusion-Pokemon-en is a English-specific latent text-to-image diffusion model capable of generating  Pokemon images given any text input.
+
+This model was trained by using a powerful text-to-image model, [diffusers](https://github.com/huggingface/diffusers)
+For more information about our training method, see [train_text_to_image.py](https://github.com/huggingface/diffusers/blob/main/examples/text_to_image/train_text_to_image.py). 
+
+<!--
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/rinnakk/japanese-stable-diffusion/blob/master/scripts/txt2img.ipynb)
+-->
+
+## Model Details
+- **Developed by:** Zhipeng Yang
+- **Model type:** Diffusion-based text-to-image generation model
+- **Language(s):** English
+- **License:** [The CreativeML OpenRAIL M license](https://huggingface.co/spaces/CompVis/stable-diffusion-license) is an [Open RAIL M license](https://www.licenses.ai/blog/2022/8/18/naming-convention-of-responsible-ai-licenses), adapted from the work that [BigScience](https://bigscience.huggingface.co/) and [the RAIL Initiative](https://www.licenses.ai/) are jointly carrying in the area of responsible AI licensing. See also [the article about the BLOOM Open RAIL license](https://bigscience.huggingface.co/blog/the-bigscience-rail-license) on which our license is based.
+- **Model Description:** This is a model that can be used to generate and modify images based on text prompts. It is a [Latent Diffusion Model (LDM)](https://arxiv.org/abs/2112.10752) that used [Stable Diffusion](https://github.com/CompVis/stable-diffusion) as a pre-trained model. 
+- **Resources for more information:** [https://github.com/svjack/Stable-Diffusion-Pokemon](https://github.com/svjack/Stable-Diffusion-Pokemon)
+
+## Examples
+
+Firstly, install our package as follows. This package is modified [🤗's Diffusers library](https://github.com/huggingface/diffusers) to run English Stable Diffusion.
+
+
+```bash
+pip install diffusers==0.4.1
+```
+
+Run this command to log in with your HF Hub token if you haven't before:
+
+```bash
+huggingface-cli login
+```
+
+Running the pipeline with the LMSDiscreteScheduler scheduler:
+
+```python
+import torch
+import pandas as pd
+
+from torch import autocast
+from diffusers import LMSDiscreteScheduler, StableDiffusionPipeline
+
+scheduler = LMSDiscreteScheduler(beta_start=0.00085, beta_end=0.012,
+     beta_schedule="scaled_linear", num_train_timesteps=1000)
+
+#pretrained_model_name_or_path = "en_model_26000"
+pretrained_model_name_or_path = "svjack/Stable-Diffusion-Pokemon-en"
+pipe = StableDiffusionPipeline.from_pretrained(pretrained_model_name_or_path,
+                                                           scheduler=scheduler, use_auth_token=True)
+
+pipe = pipe.to("cuda")
+
+disable safety_checker
+pipe.safety_checker = lambda images, clip_input: (images, False)
+
+imgs = pipe("A cartoon character with a potted plant on his head",
+                    num_inference_steps = 100
+)
+image = imgs.images[0]
+    
+image.save("output.png")
+```
+
+### Generator Results comparison
+[https://github.com/svjack/Stable-Diffusion-Pokemon](https://github.com/svjack/Stable-Diffusion-Pokemon)
+
+![0](https://github.com/svjack/Stable-Diffusion-Pokemon/blob/main/imgs/en_plant.jpg?raw=true)
+![1](https://github.com/svjack/Stable-Diffusion-Pokemon/blob/main/imgs/en_bird.jpg?raw=true)
+![2](https://github.com/svjack/Stable-Diffusion-Pokemon/blob/main/imgs/en_blue_dragon.jpg?raw=true)
+
+
+
+<!--
+<table><caption>Images</caption>
+<thead>
+<tr>
+<th>Prompt</th>
+<th colspan="1">English</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td>A cartoon character with a potted plant on his head<br/><br/>鉢植えの植物を頭に載せた漫画のキャラクター<br/><br/>一个头上戴着盆栽的卡通人物</td>
+<td><img src="https://github.com/svjack/Stable-Diffusion-Pokemon/blob/main/imgs/en_bird.jpg" alt="Girl in a jacket" width="500" height="500"></td>
+</tr>
+<tr>
+<td>cartoon bird<br/><br/>漫画の鳥<br/><br/>卡通鸟</td>
+<td><img src="en_bird.jpg" alt="Girl in a jacket" width="500" height="500"></td>
+</tr>
+</tbody>
+<tfoot>
+<tr>
+<td>blue dragon illustration<br/><br/>ブルードラゴンのイラスト<br/><br/>蓝色的龙图</td>
+<td><img src="en_blue_dragon.jpg" alt="Girl in a jacket" width="500" height="500"></td>
+</tr>
+</tfoot>
+</table>
+-->
+
+<!--
+_Note: `JapaneseStableDiffusionPipeline` is almost same as diffusers' `StableDiffusionPipeline` but added some lines to initialize our models properly._ 
+
+
+## Misuse, Malicious Use, and Out-of-Scope Use
+_Note: This section is taken from the [DALLE-MINI model card](https://huggingface.co/dalle-mini/dalle-mini), but applies in the same way to Stable Diffusion v1._
+
+
+The model should not be used to intentionally create or disseminate images that create hostile or alienating environments for people. This includes generating images that people would foreseeably find disturbing, distressing, or offensive; or content that propagates historical or current stereotypes.
+
+### Out-of-Scope Use
+The model was not trained to be factual or true representations of people or events, and therefore using the model to generate such content is out-of-scope for the abilities of this model.
+
+### Misuse and Malicious Use
+Using the model to generate content that is cruel to individuals is a misuse of this model. This includes, but is not limited to:
+
+- Generating demeaning, dehumanizing, or otherwise harmful representations of people or their environments, cultures, religions, etc.
+- Intentionally promoting or propagating discriminatory content or harmful stereotypes.
+- Impersonating individuals without their consent.
+- Sexual content without consent of the people who might see it.
+- Mis- and disinformation
+- Representations of egregious violence and gore
+- Sharing of copyrighted or licensed material in violation of its terms of use.
+- Sharing content that is an alteration of copyrighted or licensed material in violation of its terms of use.
+
+## Limitations and Bias
+
+### Limitations
+
+- The model does not achieve perfect photorealism
+- The model cannot render legible text
+- The model does not perform well on more difficult tasks which involve compositionality, such as rendering an image corresponding to “A red cube on top of a blue sphere”
+- Faces and people in general may not be generated properly.
+- The model was trained mainly with Japanese captions and will not work as well in other languages.
+- The autoencoding part of the model is lossy
+- The model was trained on a subset of a large-scale dataset
+  [LAION-5B](https://laion.ai/blog/laion-5b/) which contains adult material
+  and is not fit for product use without additional safety mechanisms and
+  considerations.
+- No additional measures were used to deduplicate the dataset. As a result, we observe some degree of memorization for images that are duplicated in the training data.
+  The training data can be searched at [https://rom1504.github.io/clip-retrieval/](https://rom1504.github.io/clip-retrieval/) to possibly assist in the detection of memorized images.
+
+### Bias
+
+While the capabilities of image generation models are impressive, they can also reinforce or exacerbate social biases. 
+Japanese Stable Diffusion was trained on Japanese datasets including [LAION-5B](https://laion.ai/blog/laion-5b/) with Japanese captions, 
+which consists of images that are primarily limited to Japanese descriptions. 
+Texts and images from communities and cultures that use other languages are likely to be insufficiently accounted for. 
+This affects the overall output of the model.
+Further, the ability of the model to generate content with non-Japanese prompts is significantly worse than with Japanese-language prompts.
+
+### Safety Module
+
+The intended use of this model is with the [Safety Checker](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/stable_diffusion/safety_checker.py) in Diffusers. 
+This checker works by checking model outputs against known hard-coded NSFW concepts.
+The concepts are intentionally hidden to reduce the likelihood of reverse-engineering this filter.
+Specifically, the checker compares the class probability of harmful concepts in the embedding space of the `CLIPTextModel` *after generation* of the images. 
+The concepts are passed into the model with the generated image and compared to a hand-engineered weight for each NSFW concept.
+
+
+## Training
+
+**Training Data**
+We used the following dataset for training the model:
+
+- Approximately 100 million images with Japanese captions, including the Japanese subset of [LAION-5B](https://laion.ai/blog/laion-5b/).
+
+**Training Procedure**
+Japanese Stable Diffusion has the same architecture as Stable Diffusion and was trained by using Stable Diffusion. Because Stable Diffusion was trained on English dataset and the CLIP tokenizer is basically for English, we had 2 stages to transfer to a language-specific model, inspired by [PITI](https://arxiv.org/abs/2205.12952).
+
+1. Train a Japanese-specific text encoder with our Japanese tokenizer from scratch with the latent diffusion model fixed. This stage is expected to map Japanese captions to Stable Diffusion's latent space. 
+2. Fine-tune the text encoder and the latent diffusion model jointly. This stage is expected to generate Japanese-style images more. 
+
+[//]: # (_Note: Japanese Stable Diffusion is still running and this checkpoint is the current best one. We might update to a better checkpoint via this repository._)
+-->

Stable-Diffusion-Pokemon-en/model_index.json

@@ -0,0 +1,32 @@
+{
+  "_class_name": "StableDiffusionPipeline",
+  "_diffusers_version": "0.4.1",
+  "feature_extractor": [
+    "transformers",
+    "CLIPImageProcessor"
+  ],
+  "safety_checker": [
+    "stable_diffusion",
+    "StableDiffusionSafetyChecker"
+  ],
+  "scheduler": [
+    "diffusers",
+    "LMSDiscreteScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "unet": [
+    "diffusers",
+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

asd.py

@@ -0,0 +1,47 @@
+import os
+from huggingface_hub import HfApi, CommitOperationDelete
+
+api = HfApi()
+repo_id = "asdasdasd1234567890/diffusers"
+local_folder = "."
+
+# 1. Get the list of files currently in the remote repository
+print("Fetching remote file list...")
+remote_files = set(api.list_repo_files(repo_id=repo_id, repo_type="model"))
+
+# 2. Get the list of files currently in your local folder
+print("Scanning local files...")
+local_files = set()
+for root, dirs, files in os.walk(local_folder):
+    for file in files:
+        rel_path = os.path.relpath(os.path.join(root, file), local_folder)
+        local_files.add(rel_path.replace(os.sep, '/'))
+
+# 3. Identify files to delete (In remote, but NOT in local)
+# Always keep .gitattributes to avoid breaking LFS tracking
+files_to_delete = remote_files - local_files - {".gitattributes", "asd.py"}
+
+# 4. Perform the deletion using CommitOperationDelete
+if files_to_delete:
+    print(f"Deleting {len(files_to_delete)} orphaned files from remote...")
+    
+    operations = [CommitOperationDelete(path_in_repo=file) for file in files_to_delete]
+    
+    api.create_commit(
+        repo_id=repo_id,
+        operations=operations,
+        commit_message=f"Clean up {len(files_to_delete)} orphaned files",
+        repo_type="model"
+    )
+else:
+    print("No files to delete.")
+
+# 5. Proceed with the stable large folder upload
+print("Starting large folder upload...")
+api.upload_large_folder(
+    folder_path=local_folder,
+    repo_id=repo_id,
+    repo_type="model",
+)
+
+print("Sync complete!")

asdf.py

@@ -0,0 +1,5 @@
+from huggingface_hub import list_repo_files
+
+files = list_repo_files(repo_id="asdasdasd1234567890/diffusers")
+print(f"Total files: {len(files)}")
+print(files)

counterfeit-v1.0/README.md

@@ -0,0 +1,22 @@
+---
+license: creativeml-openrail-m
+tags:
+- stable-diffusion
+- stable-diffusion-diffusers
+- text-to-image
+- diffusers
+inference: true
+---
+
+Counterfeit is anime style Stable Diffusion model.
+
+ e.g.
+prompt: solo,(a girl),cowboy shot,((masterpiece)),((best quality)),((an extremely detailed))  
+negative: low quality, lowres, worst quality, normal quality,(bad anatomy)  
+Steps: 28 Sampler: Euler a CFG scale: 12 Size: 640x960
+![sample1](https://huggingface.co/gsdf/counterfeit-v1.0/resolve/main/sumple01.png)
+
+prompt: solo,(a loli girl),cowboy shot,((masterpiece)),((best quality)),((an extremely detailed))  
+negative: low quality, lowres, worst quality, normal quality,(bad anatomy)  
+Steps: 28 Sampler: Euler a CFG scale: 12 Size: 640x960
+![sample2](https://huggingface.co/gsdf/counterfeit-v1.0/resolve/main/sumple02.png)

counterfeit-v1.0/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
+  }
+}

counterfeit-v1.0/logs/text2image-fine-tune/1671001219.2232141/hparams.yml

@@ -0,0 +1,37 @@
+adam_beta1: 0.9
+adam_beta2: 0.999
+adam_epsilon: 1.0e-08
+adam_weight_decay: 0.01
+cache_dir: null
+caption_column: text
+center_crop: true
+dataset_config_name: null
+dataset_name: null
+gradient_accumulation_steps: 4
+gradient_checkpointing: true
+hub_model_id: null
+hub_token: null
+image_column: null
+learning_rate: 1.0e-05
+local_rank: -1
+logging_dir: logs
+lr_scheduler: constant
+lr_warmup_steps: 0
+max_grad_norm: 1.0
+max_train_samples: null
+max_train_steps: 1500
+mixed_precision: fp16
+num_train_epochs: 7
+output_dir: /content/drive/MyDrive/stable_diffusion/fine_turning/fine_diffusion
+pretrained_model_name_or_path: Linaqruf/anything-v3.0
+push_to_hub: null
+random_flip: false
+report_to: tensorboard
+resolution: 512
+scale_lr: false
+seed: 512
+train_batch_size: 1
+train_data_dir: /content/drive/MyDrive/AI/ART_model_04
+use_8bit_adam: true
+use_ema: true
+use_xformers: true

counterfeit-v1.0/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",
+    "PNDMScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "unet": [
+    "diffusers",
+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

counterfeit-v1.0/safety_checker/config.json

@@ -0,0 +1,181 @@
+{
+  "_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",
+  "projection_dim": 768,
+  "text_config": {
+    "_name_or_path": "",
+    "add_cross_attention": false,
+    "architectures": null,
+    "attention_dropout": 0.0,
+    "bad_words_ids": null,
+    "begin_suppress_tokens": null,
+    "bos_token_id": 0,
+    "chunk_size_feed_forward": 0,
+    "cross_attention_hidden_size": null,
+    "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,
+    "exponential_decay_length_penalty": null,
+    "finetuning_task": null,
+    "forced_bos_token_id": null,
+    "forced_eos_token_id": null,
+    "hidden_act": "quick_gelu",
+    "hidden_size": 768,
+    "id2label": {
+      "0": "LABEL_0",
+      "1": "LABEL_1"
+    },
+    "initializer_factor": 1.0,
+    "initializer_range": 0.02,
+    "intermediate_size": 3072,
+    "is_decoder": false,
+    "is_encoder_decoder": false,
+    "label2id": {
+      "LABEL_0": 0,
+      "LABEL_1": 1
+    },
+    "layer_norm_eps": 1e-05,
+    "length_penalty": 1.0,
+    "max_length": 20,
+    "max_position_embeddings": 77,
+    "min_length": 0,
+    "model_type": "clip_text_model",
+    "no_repeat_ngram_size": 0,
+    "num_attention_heads": 12,
+    "num_beam_groups": 1,
+    "num_beams": 1,
+    "num_hidden_layers": 12,
+    "num_return_sequences": 1,
+    "output_attentions": false,
+    "output_hidden_states": false,
+    "output_scores": false,
+    "pad_token_id": 1,
+    "prefix": null,
+    "problem_type": null,
+    "projection_dim": 512,
+    "pruned_heads": {},
+    "remove_invalid_values": false,
+    "repetition_penalty": 1.0,
+    "return_dict": true,
+    "return_dict_in_generate": false,
+    "sep_token_id": null,
+    "suppress_tokens": null,
+    "task_specific_params": null,
+    "temperature": 1.0,
+    "tf_legacy_loss": false,
+    "tie_encoder_decoder": false,
+    "tie_word_embeddings": true,
+    "tokenizer_class": null,
+    "top_k": 50,
+    "top_p": 1.0,
+    "torch_dtype": null,
+    "torchscript": false,
+    "transformers_version": "4.25.1",
+    "typical_p": 1.0,
+    "use_bfloat16": false,
+    "vocab_size": 49408
+  },
+  "text_config_dict": {
+    "hidden_size": 768,
+    "intermediate_size": 3072,
+    "num_attention_heads": 12,
+    "num_hidden_layers": 12
+  },
+  "torch_dtype": "float32",
+  "transformers_version": null,
+  "vision_config": {
+    "_name_or_path": "",
+    "add_cross_attention": false,
+    "architectures": null,
+    "attention_dropout": 0.0,
+    "bad_words_ids": null,
+    "begin_suppress_tokens": null,
+    "bos_token_id": null,
+    "chunk_size_feed_forward": 0,
+    "cross_attention_hidden_size": null,
+    "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,
+    "exponential_decay_length_penalty": null,
+    "finetuning_task": null,
+    "forced_bos_token_id": null,
+    "forced_eos_token_id": null,
+    "hidden_act": "quick_gelu",
+    "hidden_size": 1024,
+    "id2label": {
+      "0": "LABEL_0",
+      "1": "LABEL_1"
+    },
+    "image_size": 224,
+    "initializer_factor": 1.0,
+    "initializer_range": 0.02,
+    "intermediate_size": 4096,
+    "is_decoder": false,
+    "is_encoder_decoder": false,
+    "label2id": {
+      "LABEL_0": 0,
+      "LABEL_1": 1
+    },
+    "layer_norm_eps": 1e-05,
+    "length_penalty": 1.0,
+    "max_length": 20,
+    "min_length": 0,
+    "model_type": "clip_vision_model",
+    "no_repeat_ngram_size": 0,
+    "num_attention_heads": 16,
+    "num_beam_groups": 1,
+    "num_beams": 1,
+    "num_channels": 3,
+    "num_hidden_layers": 24,
+    "num_return_sequences": 1,
+    "output_attentions": false,
+    "output_hidden_states": false,
+    "output_scores": false,
+    "pad_token_id": null,
+    "patch_size": 14,
+    "prefix": null,
+    "problem_type": null,
+    "projection_dim": 512,
+    "pruned_heads": {},
+    "remove_invalid_values": false,
+    "repetition_penalty": 1.0,
+    "return_dict": true,
+    "return_dict_in_generate": false,
+    "sep_token_id": null,
+    "suppress_tokens": null,
+    "task_specific_params": null,
+    "temperature": 1.0,
+    "tf_legacy_loss": false,
+    "tie_encoder_decoder": false,
+    "tie_word_embeddings": true,
+    "tokenizer_class": null,
+    "top_k": 50,
+    "top_p": 1.0,
+    "torch_dtype": null,
+    "torchscript": false,
+    "transformers_version": "4.25.1",
+    "typical_p": 1.0,
+    "use_bfloat16": false
+  },
+  "vision_config_dict": {
+    "hidden_size": 1024,
+    "intermediate_size": 4096,
+    "num_attention_heads": 16,
+    "num_hidden_layers": 24,
+    "patch_size": 14
+  }
+}

counterfeit-v1.0/scheduler/scheduler_config.json

@@ -0,0 +1,13 @@
+{
+  "_class_name": "PNDMScheduler",
+  "_diffusers_version": "0.10.2",
+  "beta_end": 0.012,
+  "beta_schedule": "scaled_linear",
+  "beta_start": 0.00085,
+  "num_train_timesteps": 1000,
+  "prediction_type": "epsilon",
+  "set_alpha_to_one": false,
+  "skip_prk_steps": true,
+  "steps_offset": 1,
+  "trained_betas": null
+}

counterfeit-v1.0/text_encoder/config.json

@@ -0,0 +1,25 @@
+{
+  "_name_or_path": "Linaqruf/anything-v3.0",
+  "architectures": [
+    "CLIPTextModel"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 0,
+  "dropout": 0.0,
+  "eos_token_id": 2,
+  "hidden_act": "quick_gelu",
+  "hidden_size": 768,
+  "initializer_factor": 1.0,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 77,
+  "model_type": "clip_text_model",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "projection_dim": 768,
+  "torch_dtype": "float16",
+  "transformers_version": "4.25.1",
+  "vocab_size": 49408
+}

counterfeit-v1.0/tokenizer/special_tokens_map.json

@@ -0,0 +1,24 @@
+{
+  "bos_token": {
+    "content": "<|startoftext|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<|endoftext|>",
+  "unk_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}

counterfeit-v1.0/tokenizer/tokenizer_config.json

@@ -0,0 +1,34 @@
+{
+  "add_prefix_space": false,
+  "bos_token": {
+    "__type": "AddedToken",
+    "content": "<|startoftext|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "do_lower_case": true,
+  "eos_token": {
+    "__type": "AddedToken",
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "errors": "replace",
+  "model_max_length": 77,
+  "name_or_path": "Linaqruf/anything-v3.0",
+  "pad_token": "<|endoftext|>",
+  "special_tokens_map_file": "./special_tokens_map.json",
+  "tokenizer_class": "CLIPTokenizer",
+  "unk_token": {
+    "__type": "AddedToken",
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}

counterfeit-v1.0/unet/config.json

@@ -0,0 +1,42 @@
+{
+  "_class_name": "UNet2DConditionModel",
+  "_diffusers_version": "0.10.2",
+  "_name_or_path": "Linaqruf/anything-v3.0",
+  "act_fn": "silu",
+  "attention_head_dim": 8,
+  "block_out_channels": [
+    320,
+    640,
+    1280,
+    1280
+  ],
+  "center_input_sample": false,
+  "cross_attention_dim": 768,
+  "down_block_types": [
+    "CrossAttnDownBlock2D",
+    "CrossAttnDownBlock2D",
+    "CrossAttnDownBlock2D",
+    "DownBlock2D"
+  ],
+  "downsample_padding": 1,
+  "dual_cross_attention": false,
+  "flip_sin_to_cos": true,
+  "freq_shift": 0,
+  "in_channels": 4,
+  "layers_per_block": 2,
+  "mid_block_scale_factor": 1,
+  "norm_eps": 1e-05,
+  "norm_num_groups": 32,
+  "num_class_embeds": null,
+  "only_cross_attention": false,
+  "out_channels": 4,
+  "sample_size": 64,
+  "up_block_types": [
+    "UpBlock2D",
+    "CrossAttnUpBlock2D",
+    "CrossAttnUpBlock2D",
+    "CrossAttnUpBlock2D"
+  ],
+  "upcast_attention": false,
+  "use_linear_projection": false
+}

counterfeit-v1.0/vae/config.json

@@ -0,0 +1,30 @@
+{
+  "_class_name": "AutoencoderKL",
+  "_diffusers_version": "0.10.2",
+  "_name_or_path": "Linaqruf/anything-v3.0",
+  "act_fn": "silu",
+  "block_out_channels": [
+    128,
+    256,
+    512,
+    512
+  ],
+  "down_block_types": [
+    "DownEncoderBlock2D",
+    "DownEncoderBlock2D",
+    "DownEncoderBlock2D",
+    "DownEncoderBlock2D"
+  ],
+  "in_channels": 3,
+  "latent_channels": 4,
+  "layers_per_block": 2,
+  "norm_num_groups": 32,
+  "out_channels": 3,
+  "sample_size": 256,
+  "up_block_types": [
+    "UpDecoderBlock2D",
+    "UpDecoderBlock2D",
+    "UpDecoderBlock2D",
+    "UpDecoderBlock2D"
+  ]
+}

inpainting-realvisxlInpainting_v5lightning/model_index.json

@@ -0,0 +1,42 @@
+{
+  "_class_name": "StableDiffusionXLInpaintPipeline",
+  "_diffusers_version": "0.27.2",
+  "feature_extractor": [
+    null,
+    null
+  ],
+  "force_zeros_for_empty_prompt": true,
+  "image_encoder": [
+    null,
+    null
+  ],
+  "requires_aesthetics_score": false,
+  "scheduler": [
+    "diffusers",
+    "EulerDiscreteScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "text_encoder_2": [
+    "transformers",
+    "CLIPTextModelWithProjection"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "tokenizer_2": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "unet": [
+    "diffusers",
+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

lolo-cute-pony-nsfw-v10-sdxl/README.md

@@ -0,0 +1,19 @@
+---
+license: other
+license_name: faipl-1.0-sd
+license_link: https://freedevproject.org/faipl-1.0-sd/
+language:
+- en
+library_name: diffusers
+pipeline_tag: text-to-image
+tags:
+- text-to-image
+- stable-diffusion
+- stable-diffusion-xl
+- anime
+- cute
+- pony
+---
+
+Original model is [here](https://civitai.com/models/730115/lolo-cute-pony-nsfw?modelVersionId=816445).
+This model created by [wowww](https://civitai.com/user/wowww).

lolo-cute-pony-nsfw-v10-sdxl/model_index.json

@@ -0,0 +1,41 @@
+{
+  "_class_name": "StableDiffusionXLPipeline",
+  "_diffusers_version": "0.31.0.dev0",
+  "feature_extractor": [
+    null,
+    null
+  ],
+  "force_zeros_for_empty_prompt": true,
+  "image_encoder": [
+    null,
+    null
+  ],
+  "scheduler": [
+    "diffusers",
+    "EulerAncestralDiscreteScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "text_encoder_2": [
+    "transformers",
+    "CLIPTextModelWithProjection"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "tokenizer_2": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "unet": [
+    "diffusers",
+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

pony-diffusion-v6-sdxl-inpainting/model_index.json

@@ -0,0 +1,33 @@
+{
+  "_class_name": "StableDiffusionXLPipeline",
+  "_diffusers_version": "0.19.3",
+  "force_zeros_for_empty_prompt": true,
+  "scheduler": [
+    "diffusers",
+    "EulerDiscreteScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "text_encoder_2": [
+    "transformers",
+    "CLIPTextModelWithProjection"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "tokenizer_2": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "unet": [
+    "diffusers",
+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

pony-v7-base-Diffusers/README.md

@@ -0,0 +1,122 @@
+---
+license: other
+license_name: pony-license
+license_link: LICENSE
+---
+
+# Pony V7
+
+# This repo is a clone of the [original](purplesmartai/pony-v7-base) with the files not needed for Diffusers format to work removed.
+
+![Pony V7](V7.webp)
+
+Pony V7 is a versatile character generation model based on AuraFlow architecture. It supports a wide range of styles and species types (humanoid, anthro, feral, and more) and handles character interactions through natural language prompts.
+
+## Fictional
+
+First, let me introduce [Fictional](https://fictional.ai) - our multimodal platform where AI Characters come alive through text, images, voice, and (soon) video. Powered by PonyV7, V6, Chroma, Seedream 4, and other advanced models, Fictional lets you discover, create, and interact with characters who live their own lives and share their own stories.
+
+Fictional is also what enables the development of models like V7, so if you're excited about the future of multimodal AI characters, please download Fictional on iOS or Android and help shape our future!
+
+- **iOS**: https://apps.apple.com/us/app/fictional/id6739802573
+- **Android**: https://play.google.com/store/apps/details?id=ai.fictional.app
+
+### Get in touch with us
+
+Please join [our Discord Server](https://discord.gg/pYsdjMfu3q) if you have questions about Fictional and Pony models.
+
+## Important model information
+
+Please check [this article](https://civitai.com/articles/19986) to learn more about why it took so long for us to ship V7 and upcoming model releases.
+
+## Model prompting
+
+This model supports a wide array of styles and aesthetics but provides an opinionated default prompt template:
+
+```
+special tags, factual description of image, stylistic description of image, additional content tags
+```
+
+### Special Tags
+
+`score_X`, `style_cluster_x`, `source_X` - warning: V7 prompting may be inconsistent, please see the article as we are working on V7.1 to address this.
+
+### Factual description of image
+
+Description of what is portrayed in the image without any stylistic indicators. Two recommendations:
+
+1. Start with a single phrase describing what you want in the image before going into details
+
+2. When referring to characters use pattern: `<species> <gender> <name> from <source>`
+
+For example "Anthro bunny female Lola Bunny from Space Jam".
+
+This model is capable of recognizing many popular and obscure characters and series.
+
+### Stylistic description of image
+
+Any information about image medium, shot type, lighting, etc. (More info TBD with captioning Colab)
+
+### Tags
+
+V7 is trained on a combination of natural language prompts and tags and is capable of understanding both, so describing the intended result using normal language works in most cases, although you can add some tags after the main prompt to boost them.
+
+### Captioning Colab
+
+To get a better understanding of V7 prompting, we are releasing a [captioning Colab](https://colab.research.google.com/drive/19PG-0ltob8EynxUZSwOdjMFmqyJ7ZOCB) with all the models used for V7 captioning.
+
+## Supported inference settings
+
+V7 supports resolutions in the range of 768px to 1536px. It is recommended to go for higher resolutions and at least 30 steps during inference.
+
+## Highlights compared to V6
+
+- Much stronger understanding of prompts, especially when it comes to spatial information and multiple characters
+- Much stronger background support - both generation of backgrounds and using background with character
+- Much stronger realism support out of the box
+- Ability to generate very dark and very light images
+- Resolution up to 1536x1536 pixels
+- Expanded character recognition (some V6 characters may get less recognized, but generally we extended the knowledge by a lot)
+
+## Special thanks
+
+- Iceman for helping to procure necessary training resources
+- [Simo Ryu](https://x.com/cloneofsimo) and the rest of FAL.ai team for creating AuraFlow and emotional support
+- [Runpod for providing captioning compute](https://runpod.io/?utm_source=purplesmartai)
+- [Piclumen](https://www.piclumen.com/) for being our partners
+- [City96](https://github.com/city96) for help with GGUF support
+- [diffusers](https://huggingface.co/docs/diffusers/en/index) team for supporting AuraFlow integration work
+- PSAI Server Subscribers for supporting the project costs
+- PSAI Server Moderators for being vigilant and managing the community
+- Many supporters that decided to remain anonymous but their help has been critical for getting V7 done
+
+## Technical details
+
+The model has been trained on ~10M images aesthetically ranked and selected from a superset of over 30M images with roughly 1:1 ratio between anime/cartoon/furry/pony datasets and 1:1 ratio between safe/questionable/explicit ratings. 100% of all images have been tagged and captioned with high quality detailed captions.
+
+All images have been used in training with both captions and tags. Artists' names have been removed and source data has been filtered based on our Opt-in/Opt-out program. Any inappropriate explicit content has been filtered out.
+
+## Limitations
+
+- This model does not support text generation and has degraded text generation capabilities compared to base AuraFlow
+- Special tags (including quality tags) have much weaker performance compared to V6, meaning score_9 would not necessarily yield better results on some prompts. We are working on a V7.1 follow-up to improve this
+- Small details and especially faces may degrade significantly depending on art style, this is a combination of outdated VAE and insufficient training which we are trying to improve in V7.1
+
+## LoRA training
+
+We recommend using SimpleTuner for LoRA training following [this guide](https://github.com/bghira/SimpleTuner/blob/main/documentation/quickstart/AURAFLOW.md).
+
+
+## Commercial API
+
+We provide [commercial API](https://fal.ai/models/fal-ai/pony-v7) via our exclusive partner FAL.ai
+
+## License
+
+This model is licensed under a Pony License
+
+In short, you can use this model and its outputs commercially unless you provide an inference service or application, have a company with over 1M revenue or use in professional video production. This limitations do not apply if you use first party commercial APIs.
+
+If you want to use this model commercially, please reach us at contact@purplesmart.ai.
+
+Explicit permission for commercial inference has been granted to CivitAi and Hugging Face.

pony-v7-base-Diffusers/model_index.json

@@ -0,0 +1,25 @@
+{
+  "_class_name": "AuraFlowPipeline",
+  "_diffusers_version": "0.31.0.dev0",
+  "_name_or_path": "purplesmartai/pony-v7-base",
+  "scheduler": [
+    "diffusers",
+    "FlowMatchEulerDiscreteScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "UMT5EncoderModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "LlamaTokenizerFast"
+  ],
+  "transformer": [
+    "diffusers",
+    "AuraFlowTransformer2DModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}