LLM Fine Tuning & Testing
LLM Fine Tuning
Maximize the potential of AI model integrations with comprehensive LLM fine tuning services tailored to your business requirements
Refine your LLM model
Services
Our broad range of services for fine tuning LLM models
We adeptly fine-tune large language models for businesses
For more insights, connect now-
Process Roadmapping
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Tailored Strategy
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Advanced Technologies
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Architecture Modification
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Industry-Specific Features
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Accurate & Relevant Response
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Qualitative Assessment
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Quantitative Evaluation
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Compatibility Testing
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Context-Based Output
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Improved Decision Making
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Use-Case-Based Training
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Data Cleaning & Preprocessing
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Domain-Specific Data Generation
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Data Annotation
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Risk Evaluation
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Methodological Integration
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Minimal Disruptions
Types of LLM Fine-Tuning
Varied LLM fine tuning methods offered by us
Versatility, agility, and flexibility power our solutions
Know more about our expertiseMaximize gains from AI models by identifying the right set of parameters for effective learning
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Pre-Trained Model Refinement
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Optimal Model Performance
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Balance Bias & Variance
Modify only the required fraction of the whole model by adding a new layer or using a specific dataset
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Computational Cost Reduction
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Faster Training
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Less Data Requirement
LLM instruction tuning is an if-then condition model that responds based on the keywords used
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Performance Optimization
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Versatility & Adaptability
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Reduced Hallucination
Extend the capabilities of the limited dataset by fine-tuning it for a particular use case
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Pre-Trained Model Utilization
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Improved Learning Rate
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NLP & Speech Recognition
Improve the output quality through regular human interaction and their positive & negative responses
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Goal Based Learning
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Customized Model Training
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Ethical Concern Resolution
Adapt the LLM parameters for targeted model training and generate precise content for that niche
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Efficient Resource Utilization
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Task-Based Specialization
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Business-Oriented Model Training
A strategic approach to fine tuning LLM models
Seamlessly improve the model capabilities with a dedicated team
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Data Processing
Cleaning, organizing, and formatting the data from multiple sources into a single dataset to enhance relevancy & performance
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Model Selection
Selecting a model with all the right specifications, like the primary functionality, complexity, and operation scope of the task
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03
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LLM Parameters Identification
Determine the various parameters, including the learning rate and batch size, for easy adaptation
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04
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Model Testing & Refining
Model evaluation against its performance and accuracy followed by fine-tuning it till perfect
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Deployment & Monitoring
The model is integrated into the existing system and monitored in the actual environment for further updates
Why Openxcell
We are one of the top large language model companies
We customize the technology to refine your workflow
Book a consultation-
Technical Expertise
Utilize the best-in-class resources and the latest technologies to craft progressive solutions
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Ethical Development
Ensure secure and ethical development practices for bias-free and sustainable AI solution
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15+
years of delivering quality solutions
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1000+
Happy Clients
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400+
AI Specialists
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1500+
Successful Projects
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95%
Client Retention
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20%
Faster Product Delivery
Case Study
Clients across the globe trust us with their digital solutions
We have helped businesses reach the optimal functionalities
Explore all case studies
JobTatkal - Job platform powered by Generative AI
The platform bridged the gap between recruiters and job seekers with its GPT-powered capabilities. It allowed users to create accurate job descriptions and filter results for relevant profiles. This saves recruiters’ time while candidates benefit from better visibility.
Technology Used
- Primary AI Technology - OpenAI GPT-4
- Frontend - React.js, Next.js
- Backend - Node.js
- Database - MongoDB Atlas
Key Features
- 10x Faster Profile Setup With AI
- Hiring Time Reduced By 91%
- 7x Faster Job Posting
Speed - A leading AI-powered crypto platform to ensure the security of transactions
Speed primarily aims to collaborate with AI to identify and point out suspicious crypto transactions in real time. It provides a secure environment for all users to maintain the proper crypto transactions.
Technology Used
- Data Storage - SQL/NoSQL
- Data Processing- Apache Spark
- ML Frameworks- TensorFlow and Scikit-learn
- Real-time Processing- Apache Kafka
- Deployment- Docker and Kubernetes
Key Features
- AI better the detection rate of fraudulent transactions
- Real-time analysis, minimizing potential losses
- Reduced False Positives
Cribzzzz AI Assistant - A generative AI chatbot designed for real estate
We designed a generative AI solution for Cribzzzz – a platform that connects real estate agents with potential buyers. The solution was designed to handle massive datasets and create a unique yet engaging client experience.
Technology Used
- GPT model – GPT 4
- Server – Microsoft SQL
- Frontend – ReactJS
- Backend - Dotnet Core
- Database – MongoDB
Pointers
- Generative AI-powered search
- Real-time assistance and 24/7 support
- Voice assistance and personalized suggestion
TracknTake - Discover and Deliver all products: Your Local Marketplace at Your Fingertips
The platform empowers users to search for products available in their local area. TracknTake’s beneficial feature is a flexible pick-up, which cuts wait time. It enhances the shopping experience, offering convenience and reducing delivery costs and time
Technology Used
- Backend - Python, PHP Laravel
- Frontend- Android - Kotlin, IOS- Swift
Key Features
- Find products nearby easily
- Simple search
- Instant results
- Hassle-free shopping
Industries
Industries we transform with our premium LLM fine tuning services
Get solutions that align with your niche and business requirements
Get your own custom solution
Testimonials
Here’s what our clients say about our LLM fine tuning services
We have helped our clients redefine their workflow in ways unimaginable
Resources
Recent updates and insights on LLM
Know more about the latest digital advancements
For more blogs
Frequently asked questions about
LLM fine tuning
Get all your questions answered here!
Fine-tuning is the process of reutilizing the pre-trained LLM by adding another layer of task-based specialization in a particular area or domain to increase accuracy and effectiveness.
Fine-tuning LLM requires a pre-trained model and large trainable datasets followed by parameter identification and model fine-tuning, evaluation, and refining.
Although the process looks easy, it involves many minute, complicated details and requires expert assistance. This is why it is advised to connect with the LLM fine-tuning service provider for streamlined, hassle-free upscaling.
We ensure a secure development environment and encrypt the data to prevent any security breaches. Additionally, we mandatorily sign the required legal documents before initiating the process.
Yes, we provide post-deployment maintenance at regular intervals for long-term optimal performance and relevancy.
Ready to move forward?
Contact us today to learn more about our AI solutions and start your journey towards enhanced efficiency and growth
