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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 pipeline 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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- ### Results
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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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- #### Hardware
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- #### Software
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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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- **APA:**
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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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- ## Model Card Authors [optional]
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- ## Model Card Contact
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- [More Information Needed]
 
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  library_name: diffusers
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  ---
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+ # Flux2 Klein 4b Modular repo
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+ This contains mellon config for A single-node Mellon block for the FLUX.2-klein-4B pipeline.
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+ ## How to create a modular repo?
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+ load the pipeline and save it to a new Hub repository:
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+ ```python
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+ from diffusers import ModularPipeline
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+ pipe = ModularPipeline.from_pretrained("black-forest-labs/FLUX.2-klein-4B")
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+ pipe.save_pretrained(
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+ "local/dir",
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+ repo_id="your-username/flux2-klein-auto-blocks",
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+ push_to_hub=True
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+ )
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+ ```
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+ ## Generate the Mellon Config
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+ Create and push the Mellon configuration with your desired UI types:
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+ ```python
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+ from diffusers.modular_pipelines.mellon_node_utils import MellonPipelineConfig
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+ mellon_config = MellonPipelineConfig.from_custom_block(
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+ pipe.blocks,
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+ mellon_types={
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+ "prompt": "textbox",
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+ "image": "image",
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+ "images": "image",
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+ "num_inference_steps": "number",
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+ }
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+ )
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+ mellon_config.save(
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+ local_dir="local/dir",
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+ repo_id="your-username/flux2-klein-auto-blocks",
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+ push_to_hub=True
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+ )
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+ ```
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+ ## Review and Adjust
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+ The generated `mellon_pipeline_config.json` may need adjustments. You can:
 
 
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+ - Remove inputs you don't want exposed in the UI
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+ - Add slider ranges for numeric inputs
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+ - Add dropdown options for string inputs
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+ - update default value for numeric inputs
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+ ## Use in Mellon
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+ 1. Drag a **Dynamic Block Node** from the ModularDiffusers section
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+ 2. Enter `your-username/flux2-klein-auto-blocks` as the repo_id
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+ 3. The node will show your configured inputs (prompt, image, num_inference_steps) and outputs (images)
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+ ## Supported Mellon Types
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+ | Type | Input/Output | Description |
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+ |------|--------------|-------------|
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+ | `image` | Both | Image (PIL Image) |
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+ | `textbox` | Input | Text input |
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+ | `number` | Input | Numeric input |
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+ | `slider` | Input | Slider for numeric values |
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+ | `dropdown` | Input | Dropdown selection |
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+ | `checkbox` | Input | Boolean toggle |
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+ | `text` | Both | Text display |