You will get Fast delivery for ComfyUI, Python FastAPI for Image/Video Generation


Project details
With over 4+ years of experience in building machine / deep learning models on custom datasets, fine-tuning the models to achieve optimal results, and image generation in the medical and creative domains of artificial intelligence, I can help you with your project and provide the required deliverables in time specified by the client.
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning, Recommendation SystemAI Tools
Keras, NVIDIA AI Platform, OpenCV, PyTorch, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$100
|
Standard
$200
|
Advanced
$500
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 15 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | |||
Detailed Code Comments | |||
Knowledge Graph | - | - | - |
Model Documentation | |||
Ontology | - | - | - |
Source Code | |||
Taxonomy | - | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$20 - $50
Additional Revision
+$2
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MQ
Muhammad Q.
Sep 18, 2025
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About Muawiz
Machine Learning | Deep Learning | Stable Diffusion | Agentic Workflow
100%
Job Success
Bahawalpur, Pakistan - 8:43 pm local time
Expert in building agentic LLM workflows using LangChain, RAG, and multi-modal encoders. Deeply experienced in scaling production ML via Python, FastAPI, Docker, and Kubernetes clusters with H100 GPUs. From implementing DPO and LoRAs for style transfer to managing millions of daily requests, I bridge the gap between cutting-edge R&D and scalable AI infrastructure.
Core Tech: Diffusion Models, LLMs (GPT/Gemini/Claude), RAG, Computer Vision, Kubernetes, CI/CD, DPO, Multi-modal Encoders, LangChain, FastAPI.
Steps for completing your project
After purchasing the project, send requirements so Muawiz can start the project.
Delivery time starts when Muawiz receives requirements from you.
Muawiz works on your project following the steps below.
Revisions may occur after the delivery date.
Break down the problem into chunks
Research on the each chunk

