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README_QUANTIZATION.md

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+# FLOAT8 Quantized Model (torchao)
+
+이 모델은 FP16 원본이며, 사용 시 torchao로 양자화를 적용하세요.
+
+## 원본 모델
+- Model ID: `frankjoshua/novaAnimeXL_ilV140`
+- Source: Hugging Face Hub
+
+## 양자화 정보
+- Quantization Type: **FLOAT8** (torchao)
+- Method: Weight-only quantization
+- Components: 전체 파이프라인
+- Storage Format: **safetensors** (FP16 원본)
+
+## 사용 방법
+
+```python
+from diffusers import StableDiffusionXLPipeline
+from torchao.quantization import quantize_, float8_weight_only
+import torch
+
+# 모델 로드
+pipe = StableDiffusionXLPipeline.from_pretrained(
+    "data_fp8/novaAnimeXL_fp8",
+    torch_dtype=torch.float16,
+)
+
+# GPU로 이동
+pipe = pipe.to("cuda")
+
+# FLOAT8 양자화 적용 (런타임)
+quantize_(pipe.unet, float8_weight_only())
+quantize_(pipe.vae, float8_weight_only())
+
+# 이미지 생성
+prompt = "a beautiful landscape"
+image = pipe(prompt).images[0]
+image.save("output.png")
+```
+
+## 주의사항
+- torchao 양자화는 메모리상에서만 적용됩니다
+- 모델 파일 자체는 FP16 원본입니다 (safetensors)
+- 매번 로딩할 때마다 양자화를 다시 적용해야 합니다
+- 이렇게 해도 메모리와 속도 이점은 동일합니다
+- 원본 모델 대비 메모리 사용량이 감소하고 추론 속도가 향상될 수 있습니다
+
+## 변환 도구
+- Script: `convert_hf_to_fp8_torchao.py`
+- Library: torchao

model_index.json

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+{
+  "_class_name": "StableDiffusionXLPipeline",
+  "_diffusers_version": "0.36.0",
+  "_name_or_path": "frankjoshua/novaAnimeXL_ilV140",
+  "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"
+  ]
+}

scheduler/scheduler_config.json

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+{
+  "_class_name": "EulerDiscreteScheduler",
+  "_diffusers_version": "0.36.0",
+  "beta_end": 0.012,
+  "beta_schedule": "scaled_linear",
+  "beta_start": 0.00085,
+  "clip_sample": false,
+  "final_sigmas_type": "zero",
+  "interpolation_type": "linear",
+  "num_train_timesteps": 1000,
+  "prediction_type": "epsilon",
+  "rescale_betas_zero_snr": false,
+  "sample_max_value": 1.0,
+  "set_alpha_to_one": false,
+  "sigma_max": null,
+  "sigma_min": null,
+  "skip_prk_steps": true,
+  "steps_offset": 1,
+  "timestep_spacing": "leading",
+  "timestep_type": "discrete",
+  "trained_betas": null,
+  "use_beta_sigmas": false,
+  "use_exponential_sigmas": false,
+  "use_karras_sigmas": false
+}

text_encoder/config.json

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+{
+  "architectures": [
+    "CLIPTextModel"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 0,
+  "dropout": 0.0,
+  "dtype": "float16",
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+  "hidden_act": "quick_gelu",
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+  "initializer_factor": 1.0,
+  "initializer_range": 0.02,
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+  "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,
+  "transformers_version": "5.0.0",
+  "vocab_size": 49408
+}

text_encoder/model.safetensors

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text_encoder_2/config.json

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+{
+  "architectures": [
+    "CLIPTextModelWithProjection"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 0,
+  "dropout": 0.0,
+  "dtype": "float16",
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+  "pad_token_id": 1,
+  "projection_dim": 1280,
+  "transformers_version": "5.0.0",
+  "vocab_size": 49408
+}

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tokenizer/tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": "<|startoftext|>",
+  "clean_up_tokenization_spaces": true,
+  "do_lower_case": true,
+  "eos_token": "<|endoftext|>",
+  "errors": "replace",
+  "is_local": true,
+  "model_max_length": 77,
+  "model_specific_special_tokens": {},
+  "pad_token": "<|endoftext|>",
+  "tokenizer_class": "CLIPTokenizer",
+  "unk_token": "<|endoftext|>"
+}

tokenizer_2/tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": "<|startoftext|>",
+  "clean_up_tokenization_spaces": true,
+  "do_lower_case": true,
+  "eos_token": "<|endoftext|>",
+  "errors": "replace",
+  "is_local": true,
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+  "model_specific_special_tokens": {},
+  "pad_token": "!",
+  "tokenizer_class": "CLIPTokenizer",
+  "unk_token": "<|endoftext|>"
+}

unet/config.json

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+{
+  "_class_name": "UNet2DConditionModel",
+  "_diffusers_version": "0.36.0",
+  "_name_or_path": "data/novaAnimeXL",
+  "act_fn": "silu",
+  "addition_embed_type": "text_time",
+  "addition_embed_type_num_heads": 64,
+  "addition_time_embed_dim": 256,
+  "attention_head_dim": [
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+  "cross_attention_norm": null,
+  "down_block_types": [
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+    "CrossAttnDownBlock2D",
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+  "resnet_out_scale_factor": 1.0,
+  "resnet_skip_time_act": false,
+  "resnet_time_scale_shift": "default",
+  "reverse_transformer_layers_per_block": null,
+  "sample_size": 128,
+  "time_cond_proj_dim": 256,
+  "time_embedding_act_fn": null,
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+  "time_embedding_type": "positional",
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+  "transformer_layers_per_block": [
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+    2,
+    10
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+    "CrossAttnUpBlock2D",
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+  ],
+  "upcast_attention": null,
+  "use_linear_projection": true
+}

unet/diffusion_pytorch_model.safetensors

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vae/config.json

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+  "_diffusers_version": "0.36.0",
+  "_name_or_path": "/home/seungbumhong/.cache/huggingface/hub/models--frankjoshua--novaAnimeXL_ilV140/snapshots/a9bd1371b73cb29b61536faa75ef03df38c6f96e/vae",
+  "act_fn": "silu",
+  "block_out_channels": [
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+}

vae/diffusion_pytorch_model.safetensors

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