Text-to-Image
Diffusers
StableDiffusionPipeline
stablediffusionapi.com
stable-diffusion-api
ultra-realistic
Instructions to use stablediffusionapi/realistic-vision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/realistic-vision with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/realistic-vision", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Commit ·
2f78903
1
Parent(s): d8d6500
converted using stablediffusionapi.com
Browse files- README.md +66 -0
- feature_extractor/preprocessor_config.json +1 -1
- model_index.json +2 -2
- safety_checker/config.json +2 -15
- safety_checker/pytorch_model.bin +2 -2
- scheduler/scheduler_config.json +2 -1
- text_encoder/config.json +1 -2
- text_encoder/pytorch_model.bin +2 -2
- tokenizer/tokenizer_config.json +1 -2
- unet/config.json +21 -1
- unet/diffusion_pytorch_model.bin +2 -2
- vae/config.json +2 -1
- vae/diffusion_pytorch_model.bin +2 -2
README.md
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---
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license: creativeml-openrail-m
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tags:
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- stablediffusionapi.com
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- stable-diffusion-api
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- text-to-image
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- ultra-realistic
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pinned: true
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---
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# realistic vision API Inference
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## Get API Key
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Get API key from [Stable Diffusion API](http://stablediffusionapi.com/), No Payment needed.
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Replace Key in below code, change **model_id** to "realistic-vision"
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Coding in PHP/Node/Java etc? Have a look at docs for more code examples: [View docs](https://stablediffusionapi.com/docs)
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Try model for free: [Generate Images](https://stablediffusionapi.com/models/realistic-vision)
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Model link: [View model](https://stablediffusionapi.com/models/realistic-vision)
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Credits: [View credits](https://civitai.com/?query=realistic%20vision)
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View all models: [View Models](https://stablediffusionapi.com/models)
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import requests
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import json
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url = "https://stablediffusionapi.com/api/v4/dreambooth"
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payload = json.dumps({
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"key": "your_api_key",
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"model_id": "realistic-vision",
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"prompt": "ultra realistic close up portrait ((beautiful pale cyberpunk female with heavy black eyeliner)), blue eyes, shaved side haircut, hyper detail, cinematic lighting, magic neon, dark red city, Canon EOS R3, nikon, f/1.4, ISO 200, 1/160s, 8K, RAW, unedited, symmetrical balance, in-frame, 8K",
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"negative_prompt": "painting, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, deformed, ugly, blurry, bad anatomy, bad proportions, extra limbs, cloned face, skinny, glitchy, double torso, extra arms, extra hands, mangled fingers, missing lips, ugly face, distorted face, extra legs, anime",
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"width": "512",
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"height": "512",
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"samples": "1",
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"num_inference_steps": "30",
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"safety_checker": "no",
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"enhance_prompt": "yes",
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"seed": None,
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"guidance_scale": 7.5,
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"multi_lingual": "no",
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"panorama": "no",
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"self_attention": "no",
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"upscale": "no",
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"embeddings": "embeddings_model_id",
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"lora": "lora_model_id",
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"webhook": None,
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"track_id": None
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})
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headers = {
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'Content-Type': 'application/json'
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}
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response = requests.request("POST", url, headers=headers, data=payload)
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print(response.text)
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> Use this coupon code to get 25% off **DMGG0RBN**
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feature_extractor/preprocessor_config.json
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0.4578275,
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0.40821073
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],
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"image_processor_type": "
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"image_std": [
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0.26862954,
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0.26130258,
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0.4578275,
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0.40821073
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],
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"image_processor_type": "CLIPFeatureExtractor",
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"image_std": [
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0.26862954,
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0.26130258,
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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.
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"feature_extractor": [
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"transformers",
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-
"
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],
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"requires_safety_checker": true,
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"safety_checker": [
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{
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"_class_name": "StableDiffusionPipeline",
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"_diffusers_version": "0.20.0.dev0",
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"feature_extractor": [
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"transformers",
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"CLIPFeatureExtractor"
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],
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"requires_safety_checker": true,
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"safety_checker": [
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safety_checker/config.json
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"top_p": 1.0,
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"torch_dtype": null,
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"torchscript": false,
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-
"transformers_version": "4.
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"typical_p": 1.0,
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"use_bfloat16": false,
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"vocab_size": 49408
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},
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"text_config_dict": {
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"hidden_size": 768,
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"intermediate_size": 3072,
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"num_attention_heads": 12,
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"num_hidden_layers": 12
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},
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"torch_dtype": "float32",
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"transformers_version": null,
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"vision_config": {
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"top_p": 1.0,
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"torch_dtype": null,
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"torchscript": false,
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-
"transformers_version": "4.
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"typical_p": 1.0,
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"use_bfloat16": false
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-
},
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"vision_config_dict": {
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"hidden_size": 1024,
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"intermediate_size": 4096,
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"patch_size": 14
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}
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}
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"top_p": 1.0,
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"torch_dtype": null,
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"torchscript": false,
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"transformers_version": "4.28.1",
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"typical_p": 1.0,
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"use_bfloat16": false,
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"vocab_size": 49408
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},
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"torch_dtype": "float32",
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"transformers_version": null,
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"vision_config": {
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"top_p": 1.0,
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"torch_dtype": null,
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"torchscript": false,
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"transformers_version": "4.28.1",
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"typical_p": 1.0,
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"use_bfloat16": false
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}
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}
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safety_checker/pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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-
size
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:7ba98d19732abb6b1a90fc030f61430678f9b48f5aae79be5de8e005107c8563
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size 1216065214
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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.
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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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"set_alpha_to_one": false,
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"skip_prk_steps": true,
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"steps_offset": 1,
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"trained_betas": null
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}
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{
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"_class_name": "PNDMScheduler",
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"_diffusers_version": "0.20.0.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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"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": "openai/clip-vit-large-patch14",
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"architectures": [
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"CLIPTextModel"
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],
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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.
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"vocab_size": 49408
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}
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{
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"architectures": [
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"CLIPTextModel"
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],
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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": "4.28.1",
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"vocab_size": 49408
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}
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text_encoder/pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:d5e8fe0598d0f88c3d88ae443c2060a879bc7bef007b75c9770462605dfe5e3f
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size 492307486
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tokenizer/tokenizer_config.json
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"rstrip": false,
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"single_word": false
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},
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"do_lower_case": true,
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"eos_token": {
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"__type": "AddedToken",
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},
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"errors": "replace",
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"model_max_length": 77,
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"name_or_path": "openai/clip-vit-large-patch14",
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"pad_token": "<|endoftext|>",
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-
"special_tokens_map_file": "./special_tokens_map.json",
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"tokenizer_class": "CLIPTokenizer",
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"unk_token": {
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"__type": "AddedToken",
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"rstrip": false,
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"single_word": false
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},
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"clean_up_tokenization_spaces": true,
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"do_lower_case": true,
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"eos_token": {
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"__type": "AddedToken",
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},
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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": {
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"__type": "AddedToken",
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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.
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"act_fn": "silu",
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"attention_head_dim": 8,
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"block_out_channels": [
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320,
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],
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"center_input_sample": false,
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"class_embed_type": null,
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"cross_attention_dim": 768,
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"down_block_types": [
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"CrossAttnDownBlock2D",
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"CrossAttnDownBlock2D",
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],
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"downsample_padding": 1,
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"dual_cross_attention": false,
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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_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_class_embeds": null,
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"only_cross_attention": false,
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"out_channels": 4,
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"resnet_time_scale_shift": "default",
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"sample_size": 64,
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"up_block_types": [
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"UpBlock2D",
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"CrossAttnUpBlock2D",
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{
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"_class_name": "UNet2DConditionModel",
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"_diffusers_version": "0.20.0.dev0",
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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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"block_out_channels": [
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320,
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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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],
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"downsample_padding": 1,
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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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| 32 |
"flip_sin_to_cos": true,
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"freq_shift": 0,
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"in_channels": 4,
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| 35 |
"layers_per_block": 2,
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+
"mid_block_only_cross_attention": null,
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| 37 |
"mid_block_scale_factor": 1,
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| 38 |
"mid_block_type": "UNetMidBlock2DCrossAttn",
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| 39 |
"norm_eps": 1e-05,
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"norm_num_groups": 32,
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+
"num_attention_heads": null,
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| 42 |
"num_class_embeds": null,
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"only_cross_attention": false,
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"out_channels": 4,
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| 45 |
+
"projection_class_embeddings_input_dim": null,
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| 46 |
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"resnet_out_scale_factor": 1.0,
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| 47 |
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"resnet_skip_time_act": false,
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"resnet_time_scale_shift": "default",
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"sample_size": 64,
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+
"time_cond_proj_dim": null,
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| 51 |
+
"time_embedding_act_fn": null,
|
| 52 |
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"time_embedding_dim": null,
|
| 53 |
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"time_embedding_type": "positional",
|
| 54 |
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|
| 55 |
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"transformer_layers_per_block": 1,
|
| 56 |
"up_block_types": [
|
| 57 |
"UpBlock2D",
|
| 58 |
"CrossAttnUpBlock2D",
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unet/diffusion_pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
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size 3438366838
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vae/config.json
CHANGED
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@@ -1,6 +1,6 @@
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|
| 1 |
{
|
| 2 |
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|
| 3 |
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"_diffusers_version": "0.
|
| 4 |
"act_fn": "silu",
|
| 5 |
"block_out_channels": [
|
| 6 |
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|
@@ -14,6 +14,7 @@
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|
| 14 |
"DownEncoderBlock2D",
|
| 15 |
"DownEncoderBlock2D"
|
| 16 |
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| 17 |
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| 18 |
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| 19 |
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|
| 1 |
{
|
| 2 |
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| 4 |
"act_fn": "silu",
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| 5 |
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|
| 6 |
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|
| 14 |
"DownEncoderBlock2D",
|
| 15 |
"DownEncoderBlock2D"
|
| 16 |
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| 17 |
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"force_upcast": true,
|
| 18 |
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|
| 19 |
"latent_channels": 4,
|
| 20 |
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vae/diffusion_pytorch_model.bin
CHANGED
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