TheyCallMeHex
commited on
Commit
·
4c995cd
1
Parent(s):
2cca556
Exported model to ONNX
Browse files- .gitattributes +1 -0
- README.md +63 -0
- feature_extractor/preprocessor_config.json +28 -0
- model_index.json +34 -0
- scheduler/scheduler_config.json +15 -0
- text_encoder/config.json +25 -0
- text_encoder/model.onnx +3 -0
- tokenizer/merges.txt +0 -0
- tokenizer/special_tokens_map.json +24 -0
- tokenizer/tokenizer_config.json +30 -0
- tokenizer/vocab.json +0 -0
- unet/config.json +67 -0
- unet/model.onnx +3 -0
- unet/model.onnx_data +3 -0
- vae_decoder/config.json +32 -0
- vae_decoder/model.onnx +3 -0
- vae_encoder/config.json +32 -0
- vae_encoder/model.onnx +3 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.onnx_data filter=lfs diff=lfs merge=lfs -text
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README.md
CHANGED
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---
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license: creativeml-openrail-m
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---
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---
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license: creativeml-openrail-m
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tags:
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- stable-diffusion
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- text-to-image
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---
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**Mo Di Diffusion**
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This is the fine-tuned Stable Diffusion 1.5 model trained on screenshots from a popular animation studio.
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Use the tokens **_modern disney style_** in your prompts for the effect.
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**If you enjoy my work, please consider supporting me**
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[![Become A Patreon](https://badgen.net/badge/become/a%20patron/F96854)](https://patreon.com/user?u=79196446)
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**Videogame Characters rendered with the model:**
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![Videogame Samples](https://huggingface.co/nitrosocke/mo-di-diffusion/resolve/main/modi-samples-01s.jpg)
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**Animal Characters rendered with the model:**
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![Animal Samples](https://huggingface.co/nitrosocke/mo-di-diffusion/resolve/main/modi-samples-02s.jpg)
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**Cars and Landscapes rendered with the model:**
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![Misc. Samples](https://huggingface.co/nitrosocke/mo-di-diffusion/resolve/main/modi-samples-03s.jpg)
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#### Prompt and settings for Lara Croft:
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**modern disney lara croft**
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_Steps: 50, Sampler: Euler a, CFG scale: 7, Seed: 3940025417, Size: 512x768_
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#### Prompt and settings for the Lion:
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**modern disney (baby lion) Negative prompt: person human**
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_Steps: 50, Sampler: Euler a, CFG scale: 7, Seed: 1355059992, Size: 512x512_
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This model was trained using the diffusers based dreambooth training by ShivamShrirao using prior-preservation loss and the _train-text-encoder_ flag in 9.000 steps.
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### 🧨 Diffusers
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This model can be used just like any other Stable Diffusion model. For more information,
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please have a look at the [Stable Diffusion](https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion).
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You can also export the model to [ONNX](https://huggingface.co/docs/diffusers/optimization/onnx), [MPS](https://huggingface.co/docs/diffusers/optimization/mps) and/or [FLAX/JAX]().
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```python
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from diffusers import StableDiffusionPipeline
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import torch
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model_id = "nitrosocke/mo-di-diffusion"
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pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
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pipe = pipe.to("cuda")
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prompt = "a magical princess with golden hair, modern disney style"
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image = pipe(prompt).images[0]
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image.save("./magical_princess.png")
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```
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# Gradio & Colab
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We also support a [Gradio](https://github.com/gradio-app/gradio) Web UI and Colab with Diffusers to run fine-tuned Stable Diffusion models:
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[![Open In Spaces](https://camo.githubusercontent.com/00380c35e60d6b04be65d3d94a58332be5cc93779f630bcdfc18ab9a3a7d3388/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f25463025394625413425393725323048756767696e67253230466163652d5370616365732d626c7565)](https://huggingface.co/spaces/anzorq/finetuned_diffusion)
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[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1j5YvfMZoGdDGdj3O3xRU1m4ujKYsElZO?usp=sharing)
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## License
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This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage.
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The CreativeML OpenRAIL License specifies:
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1. You can't use the model to deliberately produce nor share illegal or harmful outputs or content
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2. The authors 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
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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)
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[Please read the full license here](https://huggingface.co/spaces/CompVis/stable-diffusion-license)
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feature_extractor/preprocessor_config.json
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{
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"crop_size": {
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"height": 224,
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"width": 224
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},
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"do_center_crop": true,
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"do_convert_rgb": true,
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"feature_extractor_type": "CLIPFeatureExtractor",
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"image_mean": [
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0.48145466,
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0.4578275,
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0.40821073
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],
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"image_processor_type": "CLIPImageProcessor",
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"image_std": [
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0.26862954,
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0.26130258,
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0.27577711
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],
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"resample": 3,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"shortest_edge": 224
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}
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}
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model_index.json
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{
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"_class_name": "StableDiffusionPipeline",
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"_diffusers_version": "0.21.4",
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"_name_or_path": "mo-di-diffusion",
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"feature_extractor": [
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"transformers",
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"CLIPImageProcessor"
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],
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"requires_safety_checker": true,
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"safety_checker": [
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"stable_diffusion",
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"StableDiffusionSafetyChecker"
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],
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"scheduler": [
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"diffusers",
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"PNDMScheduler"
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],
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"text_encoder": [
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"transformers",
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"CLIPTextModel"
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],
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"tokenizer": [
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"transformers",
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"CLIPTokenizer"
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],
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"unet": [
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"diffusers",
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"UNet2DConditionModel"
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],
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"vae": [
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"diffusers",
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"AutoencoderKL"
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]
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}
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scheduler/scheduler_config.json
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{
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"_class_name": "PNDMScheduler",
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"_diffusers_version": "0.21.4",
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"beta_end": 0.012,
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"beta_schedule": "scaled_linear",
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"beta_start": 0.00085,
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"clip_sample": false,
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"num_train_timesteps": 1000,
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"prediction_type": "epsilon",
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"set_alpha_to_one": false,
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"skip_prk_steps": true,
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"steps_offset": 1,
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"timestep_spacing": "leading",
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"trained_betas": null
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}
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text_encoder/config.json
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{
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"_name_or_path": "mo-di-diffusion\\text_encoder",
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"architectures": [
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"CLIPTextModel"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 0,
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"dropout": 0.0,
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"eos_token_id": 2,
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"hidden_act": "quick_gelu",
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"hidden_size": 768,
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"initializer_factor": 1.0,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 77,
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"model_type": "clip_text_model",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"projection_dim": 768,
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"torch_dtype": "float32",
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"transformers_version": "4.34.1",
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"vocab_size": 49408
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}
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text_encoder/model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:279915781526d455c94b10fe5282e2a3e27b5832774ab16f6023155aa84ddbed
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size 492588002
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tokenizer/merges.txt
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tokenizer/special_tokens_map.json
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{
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"bos_token": {
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"content": "<|startoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "<|endoftext|>",
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"unk_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer/tokenizer_config.json
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{
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"add_prefix_space": false,
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"added_tokens_decoder": {
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"49406": {
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"content": "<|startoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"49407": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"bos_token": "<|startoftext|>",
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"clean_up_tokenization_spaces": true,
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"do_lower_case": true,
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"eos_token": "<|endoftext|>",
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"errors": "replace",
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"model_max_length": 77,
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"pad_token": "<|endoftext|>",
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"tokenizer_class": "CLIPTokenizer",
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"unk_token": "<|endoftext|>"
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}
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tokenizer/vocab.json
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unet/config.json
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{
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"_class_name": "UNet2DConditionModel",
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"_diffusers_version": "0.21.4",
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"_name_or_path": "mo-di-diffusion\\unet",
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"act_fn": "silu",
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"addition_embed_type": null,
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"addition_embed_type_num_heads": 64,
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"addition_time_embed_dim": null,
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"attention_head_dim": 8,
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"attention_type": "default",
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"block_out_channels": [
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320,
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640,
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1280,
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1280
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],
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"center_input_sample": false,
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"class_embed_type": null,
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"class_embeddings_concat": false,
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"conv_in_kernel": 3,
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"conv_out_kernel": 3,
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"cross_attention_dim": 768,
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"cross_attention_norm": null,
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"down_block_types": [
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"CrossAttnDownBlock2D",
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"CrossAttnDownBlock2D",
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"CrossAttnDownBlock2D",
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"DownBlock2D"
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],
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"downsample_padding": 1,
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31 |
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|
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|
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vae_encoder/model.onnx
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