Custom LLM Development Services

Unlock tailored domain expertise in LLM’s with Webkul’s Custom LLM Development services.


LLM’s we can train and fine-tune according to your needs

ChatGPT

ChatGPT

ChatGPT, developed by OpenAI, is an advanced language model based on the GPT architecture. It is specifically trained to engage in conversation interactions with users, providing contextually relevant and coherent responses.
Meta

Llama

LLaMA, which stands for Learning Language Model for Assistance, is a language model developed by Meta. It is designed to assist users in completing tasks and answering questions.
Gemini

Gemini

Gemini is a conversational AI model developed by Google, specifically designed for multi-turn dialogue understanding and generation. It optimizes for handling conversation exchanges involving multiple turns and diverse topics.
Mistral AI

Mistral AI

Known for its focus on portability, transparency, and cost-effective design, Mistral AI offers a comprehensive approach to utilizing LLMs. 
Anthropic

Anthropic

Anthropic aims to create AI systems that can understand and generate human-like language, with a focus on safety, transparency, and accountability.
Cohere

Cohere

Cohere is a language model designed to understand and respond to user input, using a unique approach that combines multiple AI models and techniques.

Why Choose Webkul’s Custom LLM Development Services

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Improved Accuracy

By fine-tuning on domain-specific data, custom LLMs achieve higher accuracy and relevance in their responses.
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Enhanced Efficiency

Custom LLMs streamline workflows by automating routine tasks, allowing human workers to focus on more complex and strategic activities.
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Better User Experience

Custom LLMs can be designed to understand and generate contextually relevant and user-friendly responses, significantly enhancing the user experience.
Cost Effective

Cost Savings

By automating processes and improving accuracy, custom LLMs help reduce operational costs.
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Adaptability

Custom LLMs can be continuously updated and fine-tuned to adapt to new data, trends, and user feedback, ensuring they remain relevant and effective over time.
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Scalability

Custom LLMs can be scaled to handle increasing amounts of data and interactions, making them ideal for growing businesses.

Industries using Custom LLM’s

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Custom LLM for Retail and E-commerce

Custom LLMs can help stores learn what customers like and recommend products they might enjoy. This can make shopping more fun and convenient for everyone. They can also help stores manage their stock better, so they don’t run out of popular items.

Custom LLM for Education and Training

Imagine programs that can create personalized learning materials for each student, or handle administrative tasks like grading! Custom LLMs can free up teachers’ time to focus on what they do best – helping students learn.

Custom LLM for Travel and Hospitality

Custom LLMs can be a goldmine for the travel industry. They can personalize travel recommendations for each customer, boosting satisfaction and sales. These models can also streamline operations, allowing businesses to handle inquiries and bookings more efficiently, leading to improved customer service and cost savings.

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Custom LLM for Human Resources

Custom LLMs can help companies find the best candidates for jobs and keep employees happy. They can automate routine tasks like scheduling interviews, and even analyze data to help improve employee performance.

Custom LLM for Real Estate

Finding the perfect home just got easier! Custom LLMs can help agents understand what buyers are looking for and suggest the best properties. They can also provide valuable insights into the market, so everyone can make informed decisions.

Custom LLM for Human Resources

Custom LLMs can help companies find the best candidates for jobs and keep employees happy. They can automate routine tasks like scheduling interviews, and even analyze data to help improve employee performance.

Custom LLM for Legal and Compliance

The legal industry can utilize custom LLMs to improve the efficiency, accuracy, and accessibility of legal services. These models can assist in document review, legal research, and case analysis, saving time and reducing costs.

LLM’s We Can Train and Fine Tune

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Supervised Fine-Tuning (SFT)

In supervised fine-tuning, the pre-trained LLM is further trained on a labelled dataset relevant to the target task.
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Reinforcement Learning from Human Feedback

RLHF involves training the LLM by incorporating feedback from human interactions. This technique refines the model’s responses based on human preferences and behaviour.
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Direct Preference Optimization (DPO)

DPO is a method where models are directly optimized based on user preferences without relying on intermediate reward models.
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Few-Shot Fine-Tuning

Few-shot learning enables the LLM to learn and perform new tasks with only a few examples. This technique leverages the pre-trained model’s extensive knowledge base.
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Parameter-Efficient Fine-Tuning (PEFT)

PEFT techniques aim to reduce the number of parameters that need to be updated during fine-tuning. This can be done by freezing most of the pre-trained model’s parameters.
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Task-Specific Fine-Tuning

Fine-tuning the LLM on a dataset specific to the target task, such as sentiment analysis, question answering, or language translation.

Testimonial

“The combination of this fixed rate plugin and vendor marketplace plugin perfectly meets our needs that simplified buyer’s shipping fee calculation. Just it will be even greater if Webkul could provide calculated fee per vendor on shipping cart and with API.”

Reviewed by1517573861348
Casper Wang

Director Of Development

HTC Vive

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