Upload merged model (step 3000)

README.md

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+---
+base_model: diffusers/stable-diffusion-xl-1.0-inpainting-0.1
+library_name: diffusers
+tags:
+- stable-diffusion-xl
+- inpainting
+- background-editing
+- merged
+---
+
+# refo
+
+Checkpoint **merged** (LoRA sudah di-bake ke UNet) dari `diffusers/stable-diffusion-xl-1.0-inpainting-0.1` untuk task **background editing**. Model penuh, siap pakai tanpa perlu load adapter terpisah.
+
+## Cara pakai
+
+```python
+import torch
+from diffusers import StableDiffusionXLInpaintPipeline
+
+pipe = StableDiffusionXLInpaintPipeline.from_pretrained(
+    "esalahterus/refo", torch_dtype=torch.bfloat16
+).to("cuda")
+
+result = pipe(
+    prompt="a high quality photo background, a quiet beach at sunset, photorealistic, detailed, no people, no text",
+    image=source_image, mask_image=mask_image,
+    num_inference_steps=30, guidance_scale=7.5,
+).images[0]
+```
+
+Training step: 3000

model_index.json

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+{
+  "_class_name": "StableDiffusionXLInpaintPipeline",
+  "_diffusers_version": "0.39.0",
+  "_name_or_path": "diffusers/stable-diffusion-xl-1.0-inpainting-0.1",
+  "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"
+  ]
+}

scheduler/scheduler_config.json

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+{
+  "_class_name": "EulerDiscreteScheduler",
+  "_diffusers_version": "0.39.0",
+  "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": "bfloat16",
+  "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,
+  "transformers_version": "5.13.1",
+  "vocab_size": 49408
+}

text_encoder/model.safetensors

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text_encoder_2/config.json

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+{
+  "architectures": [
+    "CLIPTextModelWithProjection"
+  ],
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+  "bos_token_id": 0,
+  "dropout": 0.0,
+  "dtype": "bfloat16",
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_size": 1280,
+  "initializer_factor": 1.0,
+  "initializer_range": 0.02,
+  "intermediate_size": 5120,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 77,
+  "model_type": "clip_text_model",
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+  "num_hidden_layers": 32,
+  "pad_token_id": 1,
+  "projection_dim": 1280,
+  "transformers_version": "5.13.1",
+  "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,
+  "local_files_only": false,
+  "model_max_length": 77,
+  "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,
+  "local_files_only": false,
+  "model_max_length": 77,
+  "pad_token": "!",
+  "tokenizer_class": "CLIPTokenizer",
+  "unk_token": "<|endoftext|>"
+}

unet/config.json

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+{
+  "_class_name": "UNet2DConditionModel",
+  "_diffusers_version": "0.39.0",
+  "_name_or_path": "/root/.cache/huggingface/hub/models--diffusers--stable-diffusion-xl-1.0-inpainting-0.1/snapshots/115134f363124c53c7d878647567d04daf26e41e/unet",
+  "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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+    20
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+  "decay": 0.9999,
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+  "resnet_time_scale_shift": "default",
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+  "time_cond_proj_dim": null,
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+  "time_embedding_type": "positional",
+  "timestep_post_act": null,
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+    10
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+    "UpBlock2D"
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vae/config.json

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+{
+  "_class_name": "AutoencoderKL",
+  "_diffusers_version": "0.39.0",
+  "_name_or_path": "/root/.cache/huggingface/hub/models--diffusers--stable-diffusion-xl-1.0-inpainting-0.1/snapshots/115134f363124c53c7d878647567d04daf26e41e/vae",
+  "act_fn": "silu",
+  "block_out_channels": [
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+    256,
+    512,
+    512
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