Fine Tuning Services
Instruction Fine-Tuning
Adjusts the model to follow specific instructions for complex tasks.
Full Fine-Tuning
Refines the entire model, retraining it on new datasets to maximize performance.
Parameter-Efficient Fine-Tuning
Modifies a subset of model parameters for quicker, cost-effective adjustments.
Transfer Learning
Uses knowledge from one domain to boost performance in another.
Multitask Learning
Fine-tunes the model to handle multiple tasks simultaneously.
Task-Specific Fine-Tuning
Optimizes the model for a particular task, such as language translation or sentiment analysis.
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.