Fine Tuning Services
Our LLM Fine-Tuning Services
LLM Model Fine Tuning Consultation
We help you understand the feasibility, scope, and impact of fine-tuning LLMs for your specific use case guiding you through the process with expert insights.
Model Selection & Training
From choosing the right base model (GPT, LLaMA, Claude, etc.) to defining training pipelines and infrastructure, we architect a solution that fits your goals and scale.
Data Selection, Preparation & Augmentation
We identify, clean, label, and augment datasets to ensure your model learns from diverse and high-quality data minimizing bias and maximizing relevance.
LLM Model Fine-Tuning & Optimization
Using state-of-the-art techniques like PEFT, LoRA, or full fine-tuning, we customize models for your domain improving accuracy, speed, and cost-efficiency.
We Follow
LLM Fine-Tuning Methods
To deliver accurate, domain-adapted, and high-performing language models, we adopt a combination of cutting-edge fine-tuning strategies:
Supervised Fine-Tuning
We train our models using high-quality labeled datasets tailored to specific tasks or domains, ensuring the model learns from accurate examples and performs reliably in real-world scenarios.
Basic Hyperparameter Tuning
By adjusting learning rates, batch sizes, and other training parameters, we optimize model performance without overfitting balancing accuracy, speed, and efficiency.
Multi-Task Learning
Our models are trained across multiple related tasks simultaneously, enhancing their generalization capabilities and reducing the need for task-specific retraining.
Few-Shot Learning
We enable models to generalize from just a few examples, minimizing data requirements and accelerating deployment in low-resource environments.
Task-Specific Fine-Tuning
When precision matters, we fine-tune models on specific datasets and use cases, ensuring outputs are tailored, relevant, and context-aware.
Our Approach To Fine-Tuning LLM Models
We follow a strategic, results-driven methodology to fine-tune large language models (LLMs) for your unique use case:
We start by curating and cleaning high-quality datasets tailored to your domain. From filtering noise to structuring inputs, every step ensures your model learns from the best.
Not all LLMs are created equal. We evaluate various open-source and proprietary models to select the one that aligns with your performance goals, cost-efficiency, and scalability needs.
We identify and adjust key model parameters — such as learning rates, batch sizes, and optimization strategies — to steer the model toward optimal results without overfitting.
Through multiple test cycles, we measure accuracy, coherence, and relevance. Each iteration includes error analysis and fine adjustments to consistently improve performance.
Once fine-tuned, the model is deployed in your preferred environment with robust monitoring tools to track usage, spot anomalies, and keep it evolving with new data.
An Alternative Approach:
Retrieval-Augmented Generation (RAG)
In cases where traditional fine-tuning may not be the best option, Retrieval-Augmented Generation (RAG) combines natural language generation with information retrieval, providing real-time access to external knowledge sources.
Why Choose Vaidik AI for Your Fine-Tuning
At Vaidik AI, we bring deep expertise and cutting-edge methods to fine-tune LLMs according to your specific needs. Our experience across diverse industries ensures that we can customize models with unparalleled precision and efficiency. Whether you’re looking for domain-specific training, task-based refinement, or scalable solutions, Vaidik AI delivers:
Tailored Expertise
We personalize models to align with your business goals.
High-Quality Results
Our rigorous fine-tuning process ensures accuracy and consistency.
Proprietary Insights
We leverage both public and proprietary data to enhance model performance.
Our Clients
Boost LLM Efficiency with Vaidik AI’s Fine-Tuning Services
Leverage our team of domain experts to tailor models to your specific needs.
Enhance performance and accuracy with specialized fine-tuning for every industry.