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We provide LLM fine-tuning services for businesses looking to step up the performance of pre-trained language models. Our specialty is fine-tuning LLMs to achieve your particular, often very unique, business aims.
We start by understanding your objectives and the exact way you intend to use the fine-tuned LLM. Whether it is to generate content, support customers, or analyze data, the pertinent data is assembled to allow the fine-tuning to hit the narrowly defined target of your particular application.
After we grasp your requirements, we pick the most suitable finetuning LLM model to suit your specific use case. We prepare the training data by structuring it to match the desired outputs, ensuring that the LLM gets high-quality input and, as a result, accurate outputs. This stage is very important to align the model's capabilities with your business objectives.
We fine-tune LLM models using state-of-the-art techniques, adjusting the model’s parameters to guarantee it performs optimally for your application. This process includes training the model with domain-specific data, improving its understanding of the context, terminology, and language specific to your business.
Once fine-tuning is complete, we thoroughly test the model’s performance by evaluating its responses and accuracy. We run multiple rounds of testing to ensure it meets your expectations and works effectively within your existing systems.
After deployment, we continue to monitor the performance of the finetuned LLM to assess its effectiveness over time. We provide regular updates and improvements based on real-world feedback and changing requirements, making sure your model remains accurate.
Solicy has years of experience in AI development and LLM fine-tuning services. We work closely with clients across industries to develop LLM fine-tuning solutions. Our expertise ensures that the models we create work effectively in real-world applications, which improves business processes and delivers measurable results.
We have a professional team of AI and ML specialists who comprehend the technical details of adjusting large language models. To put it differently, we're top-notch when it comes to knowing everything that is related to LLMs. And given that we do know all those technical details, we also know why they are essential.
Regardless of being a large enterprise or a small business, we have scalable solutions that cater to our clients' needs. Our LLM fine-tuning services can be easily adjusted to accommodate future requirements, making them a truly long-term solution.
We have assisted companies across various fields in optimizing their LLMs, consistently delivering favorable results. Our development communication is so clear that you could almost see it, and that keeps you in the picture at every stage of development. The upshot is that if you have goals, we will help you achieve them.
Himran Zerhouni
The AI and blockchain CRM Solicy built for us transformed our sales automation. Their skill, quality, and seamless teamwork made them a great partner. Highly recommended!
Ravindra Waghmare
Co-Founder, COO at Mobisoft Infotech
Our 20-year-old site needed a full rebuild—info, membership, and commerce. Solicy stood out with their responsiveness and clear expertise across multiple areas.
Riggs Eckelberry
President & CEO at OriginClear, Inc
We had a strict launch timeline. Solicy helped finish the design, corrected errors, developed the site end-to-end, and ensured everything worked smoothly after going live.
Roger B.
Solicy provided matching professionals who adapted to our pace, offered quality from the start, and communicated well. Their low-code and design skills were valuable.
We serve a diverse range of industries — not just the ones listed below. If your sector isn’t mentioned, there’s a good chance we’ve worked in it too Let’s talk.
Finetuning an LLM is the process of taking a large language model that has already been pretrained and then training it further on specialized data for some specific task, or set of tasks, in a given domain. In some cases, the task the model is final-tuned for could also be a part of the domain it serves (e.g., generating text, providing chat responses). The overall training and LLM fine-tuning process has come to be known as foundation model adaptation.
LLM fine-tuning involves taking a pre-trained model and refining it using a dataset that aligns with your business objectives. This helps the model better understand context, language, and specific terminologies, improving its ability to perform tasks like text generation, summarization, or question answering.
Standard LLM finetuning models may not capture the subtleties of your company, lingo, or sector. When you finetune a model, it's an indication that the model has been specifically optimized for your conditions. It is also an indication that it's working well, because the types of outputs it's giving are relevant and accurate for your situation.
Yes, there is support after the fine-tuning process. This support consists of three main elements:
Monitoring model performance. We keep a close eye on how well the model is doing right after fine-tuning and over time.
Making updates based on feedback. If our customers or our internal team notice ways that the model could do better, we work together to make those improvements.
Retraining the model as your data evolves. Your company has a model that was fine-tuned on your specific data. That data is living. As it and your business evolve, we ensure that the model stays with you.
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