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README.md

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+
+---
+license: creativeml-openrail-m
+base_model: CompVis/stable-diffusion-v1-4
+datasets:
+- lambdalabs/pokemon-blip-captions
+tags:
+- stable-diffusion
+- stable-diffusion-diffusers
+- text-to-image
+- diffusers
+inference: true
+---
+    
+# Text-to-image finetuning - linhqyy/sd-pokemon-15k-model
+
+This pipeline was finetuned from **CompVis/stable-diffusion-v1-4** on the **lambdalabs/pokemon-blip-captions** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['cute hippo']: 
+
+![val_imgs_grid](./val_imgs_grid.png)
+
+
+## Pipeline usage
+
+You can use the pipeline like so:
+
+```python
+from diffusers import DiffusionPipeline
+import torch
+
+pipeline = DiffusionPipeline.from_pretrained("linhqyy/sd-pokemon-15k-model", torch_dtype=torch.float16)
+prompt = "cute hippo"
+image = pipeline(prompt).images[0]
+image.save("my_image.png")
+```
+
+## Training info
+
+These are the key hyperparameters used during training:
+
+* Epochs: 72
+* Learning rate: 1e-05
+* Batch size: 1
+* Gradient accumulation steps: 4
+* Image resolution: 512
+* Mixed-precision: fp16
+
+
+More information on all the CLI arguments and the environment are available on your [`wandb` run page](https://wandb.ai/ntnl0204/text2image-fine-tune/runs/9gqcyz6e).

checkpoint-15000/optimizer.bin

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checkpoint-15000/unet/config.json

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+{
+  "_class_name": "UNet2DConditionModel",
+  "_diffusers_version": "0.24.0.dev0",
+  "_name_or_path": "CompVis/stable-diffusion-v1-4",
+  "act_fn": "silu",
+  "addition_embed_type": null,
+  "addition_embed_type_num_heads": 64,
+  "addition_time_embed_dim": null,
+  "attention_head_dim": 8,
+  "attention_type": "default",
+  "block_out_channels": [
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+  ],
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+  "conv_in_kernel": 3,
+  "conv_out_kernel": 3,
+  "cross_attention_dim": 768,
+  "cross_attention_norm": null,
+  "down_block_types": [
+    "CrossAttnDownBlock2D",
+    "CrossAttnDownBlock2D",
+    "CrossAttnDownBlock2D",
+    "DownBlock2D"
+  ],
+  "downsample_padding": 1,
+  "dropout": 0.0,
+  "dual_cross_attention": false,
+  "encoder_hid_dim": null,
+  "encoder_hid_dim_type": null,
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+  "resnet_time_scale_shift": "default",
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+  "sample_size": 64,
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+  "time_embedding_type": "positional",
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+    "CrossAttnUpBlock2D",
+    "CrossAttnUpBlock2D",
+    "CrossAttnUpBlock2D"
+  ],
+  "upcast_attention": false,
+  "use_linear_projection": false
+}

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checkpoint-15000/unet_ema/config.json

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+  "_name_or_path": "CompVis/stable-diffusion-v1-4",
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feature_extractor/preprocessor_config.json

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model_index.json

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+  "_name_or_path": "CompVis/stable-diffusion-v1-4",
+  "feature_extractor": [
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+  "requires_safety_checker": true,
+  "safety_checker": [
+    "stable_diffusion",
+    "StableDiffusionSafetyChecker"
+  ],
+  "scheduler": [
+    "diffusers",
+    "PNDMScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
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+  "tokenizer": [
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+    "CLIPTokenizer"
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+  "unet": [
+    "diffusers",
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+  "vae": [
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+    "AutoencoderKL"
+  ]
+}

safety_checker/config.json

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text_encoder/config.json

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