Add Diffusers weights
#2
by
patrickvonplaten
- opened
- README.md +37 -1
- model_index.json +38 -0
- scheduler/scheduler_config.json +21 -0
- text_encoder/config.json +25 -0
- text_encoder/model.fp16.safetensors +3 -0
- text_encoder/model.safetensors +3 -0
- tokenizer/merges.txt +0 -0
- tokenizer/special_tokens_map.json +30 -0
- tokenizer/tokenizer_config.json +38 -0
- tokenizer/vocab.json +0 -0
- unet/config.json +73 -0
- unet/diffusion_pytorch_model.fp16.safetensors +3 -0
- unet/diffusion_pytorch_model.safetensors +3 -0
- vae/config.json +32 -0
- vae/diffusion_pytorch_model.fp16.safetensors +3 -0
- vae/diffusion_pytorch_model.safetensors +3 -0
README.md
CHANGED
@@ -61,6 +61,42 @@ The model is intended for research purposes only. Possible research areas and ta
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Excluded uses are described below.
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### Out-of-Scope Use
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The model was not trained to be factual or true representations of people or events,
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## How to Get Started with the Model
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-
Check out https://github.com/Stability-AI/generative-models
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Excluded uses are described below.
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### Diffusers
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```
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pip install diffusers transformers accelerate --upgrade
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```
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- **Text-to-image**:
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SD-Turbo does not make use of `guidance_scale` or `negative_prompt`, we disable it with `guidance_scale=0.0`.
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Preferably, the model generates images of size 512x512 but higher image sizes work as well.
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A **single step** is enough to generate high quality images.
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```py
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from diffusers import AutoPipelineForText2Image
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import torch
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pipe = AutoPipelineForText2Image.from_pretrained("stabilityai/sd-turbo", torch_dtype=torch.float16, variant="fp16")
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pipe.to("cuda")
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prompt = "A cinematic shot of a baby racoon wearing an intricate italian priest robe."
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image = pipe(prompt=prompt, num_inference_steps=1, guidance_scale=0.0).images[0]
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```
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- **Image-to-image**:
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When using SD-Turbo for image-to-image generation, make sure that `num_inference_steps` * `strength` is larger or equal
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to 1. The image-to-image pipeline will run for `int(num_inference_steps * strength)` steps, *e.g.* 0.5 * 2.0 = 1 step in our example
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below.
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```py
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from diffusers import AutoPipelineForImage2Image
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from diffusers.utils import load_image
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pipe = AutoPipelineForImage2Image.from_pretrained("stabilityai/sd-turbo", torch_dtype=torch.float16, variant="fp16")
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init_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png").resize((512, 512))
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prompt = "cat wizard, gandalf, lord of the rings, detailed, fantasy, cute, adorable, Pixar, Disney, 8k"
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image = pipe(prompt, image=init_image, num_inference_steps=2, strength=0.5, guidance_scale=0.0).images[0]
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```
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### Out-of-Scope Use
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The model was not trained to be factual or true representations of people or events,
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## How to Get Started with the Model
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Check out https://github.com/Stability-AI/generative-models
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model_index.json
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@@ -0,0 +1,38 @@
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{
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"_class_name": "StableDiffusionPipeline",
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"_diffusers_version": "0.24.0.dev0",
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"_name_or_path": "/home/patrick/sd-turbo/",
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"feature_extractor": [
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null,
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null
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],
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"image_encoder": [
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null,
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null
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],
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"requires_safety_checker": true,
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"safety_checker": [
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null,
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null
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],
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"scheduler": [
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"diffusers",
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"EulerDiscreteScheduler"
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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": "EulerDiscreteScheduler",
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"_diffusers_version": "0.24.0.dev0",
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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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"interpolation_type": "linear",
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"num_train_timesteps": 1000,
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"prediction_type": "epsilon",
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"sample_max_value": 1.0,
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"set_alpha_to_one": false,
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"sigma_max": null,
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"sigma_min": null,
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"skip_prk_steps": true,
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"steps_offset": 1,
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"timestep_spacing": "trailing",
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"timestep_type": "discrete",
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"trained_betas": null,
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"use_karras_sigmas": false
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}
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text_encoder/config.json
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{
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"_name_or_path": "/home/patrick/sd-turbo/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": "gelu",
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"hidden_size": 1024,
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"initializer_factor": 1.0,
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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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": 16,
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"num_hidden_layers": 23,
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"pad_token_id": 1,
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"projection_dim": 512,
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"torch_dtype": "float32",
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"transformers_version": "4.36.0.dev0",
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"vocab_size": 49408
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}
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text_encoder/model.fp16.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:bc1827c465450322616f06dea41596eac7d493f4e95904dcb51f0fc745c4e13f
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size 680820392
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text_encoder/model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:67e013543d4fac905c882e2993d86a2d454ee69dc9e8f37c0c23d33a48959d15
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size 1361596304
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tokenizer/merges.txt
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The diff for this file is too large to render.
See raw diff
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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": {
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"content": "!",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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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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"0": {
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"content": "!",
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"lstrip": false,
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"normalized": false,
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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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"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": "!",
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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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The diff for this file is too large to render.
See raw diff
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unet/config.json
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{
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"_class_name": "UNet2DConditionModel",
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"_diffusers_version": "0.24.0.dev0",
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"_name_or_path": "/home/patrick/sd-turbo/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": [
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5,
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10,
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20,
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20
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],
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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": 1024,
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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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"dropout": 0.0,
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"dual_cross_attention": false,
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"encoder_hid_dim": null,
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"encoder_hid_dim_type": null,
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"flip_sin_to_cos": true,
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"freq_shift": 0,
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"in_channels": 4,
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"layers_per_block": 2,
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"mid_block_only_cross_attention": null,
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"mid_block_scale_factor": 1,
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"mid_block_type": "UNetMidBlock2DCrossAttn",
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"norm_eps": 1e-05,
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"norm_num_groups": 32,
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"num_attention_heads": null,
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"num_class_embeds": null,
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"only_cross_attention": false,
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"out_channels": 4,
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"projection_class_embeddings_input_dim": null,
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"resnet_out_scale_factor": 1.0,
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"resnet_skip_time_act": false,
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"resnet_time_scale_shift": "default",
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"reverse_transformer_layers_per_block": null,
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"sample_size": 64,
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"time_cond_proj_dim": null,
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"time_embedding_act_fn": null,
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"time_embedding_dim": null,
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"time_embedding_type": "positional",
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"timestep_post_act": null,
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"transformer_layers_per_block": 1,
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"up_block_types": [
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"UpBlock2D",
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"CrossAttnUpBlock2D",
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"CrossAttnUpBlock2D",
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"CrossAttnUpBlock2D"
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],
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"upcast_attention": null,
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"use_linear_projection": true
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}
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unet/diffusion_pytorch_model.fp16.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:40ec400881e27d1376c7c95c5bd495f407b33756e80eb6365e301c33a07af6e5
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size 1731904736
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unet/diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:438da6db739c8651ec4152341b8133d6896db452ea27afdb6b9b0344f0c40532
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size 3463726504
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vae/config.json
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{
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"_class_name": "AutoencoderKL",
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"_diffusers_version": "0.24.0.dev0",
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"_name_or_path": "/home/patrick/sd-turbo/vae",
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"act_fn": "silu",
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"block_out_channels": [
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128,
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256,
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512,
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512
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],
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"down_block_types": [
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"DownEncoderBlock2D",
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"DownEncoderBlock2D",
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"DownEncoderBlock2D",
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"DownEncoderBlock2D"
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],
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"force_upcast": true,
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"in_channels": 3,
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"latent_channels": 4,
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"layers_per_block": 2,
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"norm_num_groups": 32,
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"out_channels": 3,
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"sample_size": 768,
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"scaling_factor": 0.18215,
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"up_block_types": [
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"UpDecoderBlock2D",
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"UpDecoderBlock2D",
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"UpDecoderBlock2D",
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"UpDecoderBlock2D"
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]
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}
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vae/diffusion_pytorch_model.fp16.safetensors
ADDED
@@ -0,0 +1,3 @@
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+
version https://git-lfs.github.com/spec/v1
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2 |
+
oid sha256:3e4c08995484ee61270175e9e7a072b66a6e4eeb5f0c266667fe1f45b90daf9a
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3 |
+
size 167335342
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vae/diffusion_pytorch_model.safetensors
ADDED
@@ -0,0 +1,3 @@
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+
version https://git-lfs.github.com/spec/v1
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+
oid sha256:2aa1f43011b553a4cba7f37456465cdbd48aab7b54b9348b890e8058ea7683ec
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3 |
+
size 334643268
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