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Browse files- README.md +66 -0
- model_index.json +1 -10
- scheduler/scheduler_config.json +1 -6
- text_encoder/config.json +1 -2
- text_encoder_2/config.json +1 -2
- tokenizer/special_tokens_map.json +1 -7
- tokenizer/tokenizer_config.json +23 -20
- tokenizer_2/special_tokens_map.json +1 -7
- tokenizer_2/tokenizer_config.json +23 -28
- unet/config.json +1 -3
- vae/config.json +3 -9
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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# NewDream-SDXL 2.0 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 "newdream-sdxl-20"
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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/newdream-sdxl-20)
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Model link: [View model](https://stablediffusionapi.com/models/newdream-sdxl-20)
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Credits: [View credits](https://civitai.com/?query=NewDream-SDXL%202.0)
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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": "newdream-sdxl-20",
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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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model_index.json
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{
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"_class_name": "StableDiffusionXLPipeline",
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"_diffusers_version": "0.
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"_name_or_path": "model",
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"feature_extractor": [
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null,
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null
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],
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"force_zeros_for_empty_prompt": true,
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"image_encoder": [
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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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"_class_name": "StableDiffusionXLPipeline",
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"_diffusers_version": "0.21.2",
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"force_zeros_for_empty_prompt": true,
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"scheduler": [
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"diffusers",
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"EulerDiscreteScheduler"
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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.
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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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"final_sigmas_type": "zero",
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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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"rescale_betas_zero_snr": false,
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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": "leading",
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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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{
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"_class_name": "EulerDiscreteScheduler",
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"_diffusers_version": "0.21.2",
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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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"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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"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": "model/text_encoder",
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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": "float16",
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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": "float16",
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"transformers_version": "4.33.1",
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"vocab_size": 49408
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}
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text_encoder_2/config.json
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{
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"_name_or_path": "model/text_encoder_2",
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"architectures": [
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"CLIPTextModelWithProjection"
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],
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"pad_token_id": 1,
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"projection_dim": 1280,
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"torch_dtype": "float16",
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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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"CLIPTextModelWithProjection"
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],
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"pad_token_id": 1,
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"projection_dim": 1280,
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"torch_dtype": "float16",
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"transformers_version": "4.33.1",
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"vocab_size": 49408
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}
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tokenizer/special_tokens_map.json
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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": "<|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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"unk_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"rstrip": false,
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"single_word": false
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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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tokenizer/tokenizer_config.json
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"add_prefix_space": false,
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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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":
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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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}
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{
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"bos_token": {
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"__type": "AddedToken",
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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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"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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"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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"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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"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_2/special_tokens_map.json
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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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"single_word": false
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"unk_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"rstrip": false,
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"single_word": false
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"pad_token": "!",
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"unk_token": {
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"lstrip": false,
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tokenizer_2/tokenizer_config.json
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{
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"add_prefix_space": false,
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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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"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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}
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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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"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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"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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| 20 |
+
},
|
| 21 |
"errors": "replace",
|
| 22 |
"model_max_length": 77,
|
| 23 |
"pad_token": "!",
|
| 24 |
"tokenizer_class": "CLIPTokenizer",
|
| 25 |
+
"unk_token": {
|
| 26 |
+
"__type": "AddedToken",
|
| 27 |
+
"content": "<|endoftext|>",
|
| 28 |
+
"lstrip": false,
|
| 29 |
+
"normalized": true,
|
| 30 |
+
"rstrip": false,
|
| 31 |
+
"single_word": false
|
| 32 |
+
}
|
| 33 |
}
|
unet/config.json
CHANGED
|
@@ -1,7 +1,6 @@
|
|
| 1 |
{
|
| 2 |
"_class_name": "UNet2DConditionModel",
|
| 3 |
-
"_diffusers_version": "0.
|
| 4 |
-
"_name_or_path": "model/unet",
|
| 5 |
"act_fn": "silu",
|
| 6 |
"addition_embed_type": "text_time",
|
| 7 |
"addition_embed_type_num_heads": 64,
|
|
@@ -51,7 +50,6 @@
|
|
| 51 |
"resnet_out_scale_factor": 1.0,
|
| 52 |
"resnet_skip_time_act": false,
|
| 53 |
"resnet_time_scale_shift": "default",
|
| 54 |
-
"reverse_transformer_layers_per_block": null,
|
| 55 |
"sample_size": 128,
|
| 56 |
"time_cond_proj_dim": null,
|
| 57 |
"time_embedding_act_fn": null,
|
|
|
|
| 1 |
{
|
| 2 |
"_class_name": "UNet2DConditionModel",
|
| 3 |
+
"_diffusers_version": "0.21.2",
|
|
|
|
| 4 |
"act_fn": "silu",
|
| 5 |
"addition_embed_type": "text_time",
|
| 6 |
"addition_embed_type_num_heads": 64,
|
|
|
|
| 50 |
"resnet_out_scale_factor": 1.0,
|
| 51 |
"resnet_skip_time_act": false,
|
| 52 |
"resnet_time_scale_shift": "default",
|
|
|
|
| 53 |
"sample_size": 128,
|
| 54 |
"time_cond_proj_dim": null,
|
| 55 |
"time_embedding_act_fn": null,
|
vae/config.json
CHANGED
|
@@ -1,7 +1,6 @@
|
|
| 1 |
{
|
| 2 |
"_class_name": "AutoencoderKL",
|
| 3 |
-
"_diffusers_version": "0.
|
| 4 |
-
"_name_or_path": "model/vae",
|
| 5 |
"act_fn": "silu",
|
| 6 |
"block_out_channels": [
|
| 7 |
128,
|
|
@@ -18,20 +17,15 @@
|
|
| 18 |
"force_upcast": true,
|
| 19 |
"in_channels": 3,
|
| 20 |
"latent_channels": 4,
|
| 21 |
-
"latents_mean": null,
|
| 22 |
-
"latents_std": null,
|
| 23 |
"layers_per_block": 2,
|
| 24 |
"norm_num_groups": 32,
|
| 25 |
"out_channels": 3,
|
| 26 |
-
"sample_size":
|
| 27 |
"scaling_factor": 0.13025,
|
| 28 |
-
"shift_factor": null,
|
| 29 |
"up_block_types": [
|
| 30 |
"UpDecoderBlock2D",
|
| 31 |
"UpDecoderBlock2D",
|
| 32 |
"UpDecoderBlock2D",
|
| 33 |
"UpDecoderBlock2D"
|
| 34 |
-
]
|
| 35 |
-
"use_post_quant_conv": true,
|
| 36 |
-
"use_quant_conv": true
|
| 37 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"_class_name": "AutoencoderKL",
|
| 3 |
+
"_diffusers_version": "0.21.2",
|
|
|
|
| 4 |
"act_fn": "silu",
|
| 5 |
"block_out_channels": [
|
| 6 |
128,
|
|
|
|
| 17 |
"force_upcast": true,
|
| 18 |
"in_channels": 3,
|
| 19 |
"latent_channels": 4,
|
|
|
|
|
|
|
| 20 |
"layers_per_block": 2,
|
| 21 |
"norm_num_groups": 32,
|
| 22 |
"out_channels": 3,
|
| 23 |
+
"sample_size": 1024,
|
| 24 |
"scaling_factor": 0.13025,
|
|
|
|
| 25 |
"up_block_types": [
|
| 26 |
"UpDecoderBlock2D",
|
| 27 |
"UpDecoderBlock2D",
|
| 28 |
"UpDecoderBlock2D",
|
| 29 |
"UpDecoderBlock2D"
|
| 30 |
+
]
|
|
|
|
|
|
|
| 31 |
}
|