Update README.md

README.md

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 library_name: diffusers
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
+# Model Card for Flux Dev FP8 Pipeline
 
+This diffusers pipeline is a complete implementation of the Flux Dev 1 model optimized for FP8 precision, specifically designed for deployment on AWS SageMaker for integration with ComfyUI through a custom node. Unlike a model-only repository, this contains the full pipeline architecture required for proper deployment.
 
 ## Model Details
 
-### Model Description
+### Pipeline Description
 
-<!-- Provide a longer summary of what this model is. -->
+This repository contains a complete diffusers pipeline implementation utilizing the Flux Dev 1 model optimized for FP8 precision. Unlike model-only repositories, this provides the entire pipeline architecture required for text-to-image generation, properly structured for SageMaker deployment and ComfyUI integration.
 
-This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
+The pipeline was created to address the lack of publicly available FP8 Flux Dev implementations suitable for deployment, as standard approaches to model loading create symlink issues that prevent proper SageMaker packaging.
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+- **Developed by:** Jlonge4
+- **Pipeline type:** Complete Text-to-Image Diffusion Pipeline (FP8 Optimized)
+- **Model component:** Flux Dev 1 quantized to FP8
+- **License:** Same as original Flux Dev 1 model
+- **Base model:** [Comfy-Org/flux1-dev](https://huggingface.co/Comfy-Org/flux1-dev)
 
-### Model Sources [optional]
+### Model Sources
 
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Pipeline:** [Jlonge4/flux-dev-fp8](https://huggingface.co/Jlonge4/flux-dev-fp8)
+- **Original Model:** [Comfy-Org/flux1-dev](https://huggingface.co/Comfy-Org/flux1-dev)
 
 ## Uses
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
 ### Direct Use
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+This model is designed to be deployed as a SageMaker endpoint and accessed through a custom ComfyUI node. It enables text-to-image generation directly within ComfyUI workflows, leveraging the performance benefits of FP8 precision and AWS's infrastructure.
 
-[More Information Needed]
+Primary use cases include:
+- Text-to-image generation within ComfyUI
+- Faster inference for Flux Dev 1 model
+- Integration with existing ComfyUI workflows
 
-### Downstream Use [optional]
+### Downstream Use
 
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
+The model can be integrated into larger creative pipelines within ComfyUI, serving as the text-to-image generation component that can be combined with other image processing and enhancement nodes.
 
 ### Out-of-Scope Use
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
+This model is not designed for:
+- Deployment outside of AWS SageMaker
+- Use cases requiring precision higher than FP8
+- Applications requiring inference time longer than SageMaker's 60-second timeout
 
 ### Recommendations
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
-
-## Training Details
-
-### Training Data
-
-<!-- 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. -->
-
-[More Information Needed]
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
+- Deploy on recommended g5.8xlarge instances for optimal performance
+- Design prompts considering the 60-second inference timeout limitation
+- Monitor inference performance and quality to identify any precision-related issues
+- Follow best practices for prompt engineering with Flux models
 
-## Evaluation
+## How to Get Started with the Pipeline
 
-<!-- This section describes the evaluation protocols and provides the results. -->
+### Deployment on SageMaker
 
-### Testing Data, Factors & Metrics
+1. Clone the repository: [ComfyUI Sagemaker Node](https://github.com/jlonge4/custom_comfy_ui/tree/main)
+2. Run the `deploy_flux_dev-pipe.ipynb` notebook to deploy the model to SageMaker
+3. Use a g5.8xlarge instance for deployment (recommended)
 
-#### Testing Data
+### Integration with ComfyUI
 
-<!-- This should link to a Dataset Card if possible. -->
+ComfyUI Sagemaker Node [repo](https://github.com/jlonge4/custom_comfy_ui/tree/main)
 
-[More Information Needed]
+1. Install the SageMaker custom node in your ComfyUI environment
+2. Find the "Text2Image" node in the node browser
+3. Connect the node to your workflow, providing a text prompt and optional parameters
+4. The node will communicate with your SageMaker endpoint to generate images
 
 #### Factors
 
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+- Generation quality compared to original model
+- Inference speed
+- Memory usage
+- Deployment reliability on SageMaker
 
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-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).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
+## Technical Specifications
 
 ### Model Architecture and Objective
 
-[More Information Needed]
+This model uses the same architecture as Flux Dev 1 but operates at FP8 precision. It addresses specific technical challenges:
 
-### Compute Infrastructure
+1. Standard HuggingFace diffusers `from_single_file` download creates symlinks that render the `model.tar.gz` unusable for SageMaker deployment
+2. A complete custom pipeline was created to properly package the model for SageMaker
+3. Special handling for FP8 precision throughout the pipeline ensures optimal performance
 
-[More Information Needed]
+### Compute Infrastructure
 
 #### Hardware
 
-[More Information Needed]
+- Recommended: AWS g5.8xlarge GPU instance
+- Minimum: GPU with 16GB+ VRAM supporting FP8 operations
 
 #### Software
 
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
+- AWS SageMaker
+- HuggingFace Diffusers
+- ComfyUI with custom SageMaker node
 
-## More Information [optional]
+## More Information
 
-[More Information Needed]
+This complete pipeline implementation was specifically created to address the challenges of deploying Flux Dev 1 to SageMaker in FP8 format for ComfyUI integration. 
 
-## Model Card Authors [optional]
+Key innovations include:
+1. Full pipeline structure with all necessary components properly organized for SageMaker deployment
+2. Avoids symlink issues that would typically occur when using HuggingFace's `from_single_file` download option 
+3. Proper packaging methodology that ensures the `model.tar.gz` works correctly when deployed as an endpoint
+4. Complete integration with SageMaker endpoint infrastructure through the ComfyUI custom node
 
-[More Information Needed]
+For updates and improvements, check the repository at [Jlonge4/flux-dev-fp8](https://huggingface.co/Jlonge4/flux-dev-fp8).
 
 ## Model Card Contact
 
-[More Information Needed]
+For questions or issues regarding this model, please open an issue on the HuggingFace repository.