Upload StableDiffusionXLPipeline
Browse files- README.md +200 -0
- model_index.json +41 -0
- scheduler/scheduler_config.json +21 -0
- text_encoder/config.json +24 -0
- text_encoder/model.safetensors +3 -0
- text_encoder_2/config.json +24 -0
- text_encoder_2/model.safetensors +3 -0
- tokenizer/merges.txt +0 -0
- tokenizer/special_tokens_map.json +30 -0
- tokenizer/tokenizer_config.json +30 -0
- tokenizer/vocab.json +0 -0
- tokenizer_2/merges.txt +0 -0
- tokenizer_2/special_tokens_map.json +24 -0
- tokenizer_2/tokenizer_config.json +38 -0
- tokenizer_2/vocab.json +0 -0
- unet/config.json +72 -0
- unet/diffusion_pytorch_model.safetensors +3 -0
- vae/config.json +34 -0
- vae/diffusion_pytorch_model.safetensors +3 -0
README.md
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---
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library_name: diffusers
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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model_index.json
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{
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"_class_name": "StableDiffusionXLPipeline",
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"_diffusers_version": "0.28.0.dev0",
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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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"text_encoder": [
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"transformers",
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"CLIPTextModel"
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],
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"text_encoder_2": [
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"transformers",
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"CLIPTextModelWithProjection"
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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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"tokenizer_2": [
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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": "0.28.0.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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"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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text_encoder/config.json
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{
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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": "float16",
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"transformers_version": "4.40.1",
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"vocab_size": 49408
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}
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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 sha256:521d1cac948d6b55329fc72887996b897e55a73f92d5a261765157dd46b6c852
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size 246144152
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text_encoder_2/config.json
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{
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"architectures": [
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"CLIPTextModelWithProjection"
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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": 1280,
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"initializer_factor": 1.0,
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"initializer_range": 0.02,
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"intermediate_size": 5120,
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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": 20,
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"num_hidden_layers": 32,
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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": "4.40.1",
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"vocab_size": 49408
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}
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text_encoder_2/model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:74a0f1a91af9ca9024b083f5aadf25c3c0f752f506e8c3469b4de6ecf73593f6
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size 1389382176
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tokenizer/merges.txt
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tokenizer/special_tokens_map.json
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1 |
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|
2 |
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|
3 |
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4 |
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|
5 |
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|
6 |
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|
7 |
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|
8 |
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13 |
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|
14 |
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15 |
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|
16 |
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|
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|
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|
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20 |
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|
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|
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|
28 |
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|
29 |
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|
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tokenizer/tokenizer_config.json
ADDED
@@ -0,0 +1,30 @@
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1 |
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{
|
2 |
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|
3 |
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|
4 |
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6 |
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|
7 |
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|
8 |
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|
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|
10 |
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|
11 |
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|
12 |
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|
13 |
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|
14 |
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|
15 |
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|
16 |
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|
17 |
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|
18 |
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|
19 |
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|
20 |
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|
21 |
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|
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|
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|
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|
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|
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|
29 |
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|
30 |
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|
tokenizer/vocab.json
ADDED
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tokenizer_2/merges.txt
ADDED
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tokenizer_2/special_tokens_map.json
ADDED
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23 |
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|
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tokenizer_2/tokenizer_config.json
ADDED
@@ -0,0 +1,38 @@
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tokenizer_2/vocab.json
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unet/config.json
ADDED
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unet/diffusion_pytorch_model.safetensors
ADDED
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vae/config.json
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vae/diffusion_pytorch_model.safetensors
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