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I will finetune, quantize, and optimize ml llm vlm models for faster, smarter ai
Akash Bhansali
About this gig
Unlock domain-specific performance by tailoring large or vision-language models, expert fine-tuning, memory-saving quantization, and deployment-ready optimization.
What You Get:
- Domain-aligned LLM/VLM model finetuned on your data
- Quantized version for lightweight deployment
- Evaluation metrics and improvement report
- Deployment and integration guidance
- Friendly support and up to 5 revisions (premium)
Why Choose Me?
- Expert in LoRA/QLoRA, Hugging Face & vLLM frameworks
- Proven experience optimizing models for speed and memory
- Transparent communication and respect for data privacy
- Flexible packages to fit startups, research projects or enterprise needs
Get to know Akash Bhansali
Akash Bhansali
Whatever it Takes
- FromIndia
- Member sinceJan 2021
- Avg. response time4 hours
- Last delivery2 years
Languages
English, Hindi, German
Looking for an expert freelancer who can provide top-notch solutions for your business needs? Look no further than me! As an experienced professional, I specialise in offering AI & Robotics solutions, Computer Vision solutions, AI Agents development, LLMs, VLMs, and much more.
Whether you're looking to automate your business processes, improve your computer vision capabilities, or develop a cutting-edge mobile application, I have the skills and expertise to help you succeed. Contact me today to learn more about how I can help you achieve your goals!
FAQ
Which models can you fine‑tune?
I work with open-source LLMs (Llama, Mistral, Falcon, Gemma) and vision-language models. We’ll discuss the best base model for your task
What is quantization and does it reduce performance?
Quantization compresses model weights from high precision to lower precision (e.g., 32‑bit → 8‑bit), cutting memory usage. When implemented carefully, the performance impact is minimal and inference speed often improves.
Do you offer parameter‑efficient fine‑tuning (LoRA/QLoRA)?
Yes! PEFT methods freeze most parameters and tune only small adapters, reducing compute requirements while delivering strong results.
How do you handle data privacy?
Your data remains confidential. I’ll sign an NDA if needed and only use your datasets for training and evaluation.
Who owns the fine‑tuned model?
You retain full rights to the fine‑tuned weights, adapters and quantized models. I do not resell or reuse your custom model.
