Introducing a Data-centric Way to Fine-tune LLMS Using Hybrid Datasets

Fine-tuning, in the realm of LLMs, is the practice of subtly adjusting your AI model to enhance its performance. LLMs trained on Bitext’s datasets can respond to user queries with a vastly improved level of precision and understanding. Bitext’s dataset consistently proves to be the ideal tuning tool, amplifying LLM capabilities in Generative AI, Conversation AI, and Q&A language models. 



Our Customers

Working with 3 of the Top 5 Largest Companies in NASDAQ

“Bitext unveils an advanced dataset of 27,000 entries, crafted to refine customer support with LLMs, now open source for all.”

Bitext Builds Datasets for Fine-tuning LLMs

Unlock the full potential of Large Language Models (LLMs) with our advanced data preparation solution. We understand that one of the critical factors in achieving exceptional performance with LLMs is the quality and relevance of the training data. That’s why we offer a comprehensive suite of tools and services specifically designed to automate and streamline the datasets for fine-tuning LLMs.

Our Data Preparation Solution Has Two Components:

1. We Leverage Your Internal Data Sources


Data Collection

We help you identify and collect high-quality datasets that align with your specific application and domain. Our team of experts assists in sourcing diverse and relevant data, ensuring that you have a robust foundation for training your LLM.

Data Cleaning and Preprocessing

Our advanced data cleaning and preprocessing techniques ensure that your training data is of the highest quality. We apply data cleaning algorithms, handle noisy or irrelevant samples, and perform any necessary data transformations to optimize the dataset for fine-tuning.


Annotation and Labeling

If your LLM requires annotated or labelled data, we offer efficient annotation services. Our experienced annotators precisely label the data based on your specific requirements, whether it’s sentiment analysis, named entity recognition, or any other custom annotation task.

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2. We Expand Your Internal Data with Synthetic Text (NLG)

Data Augmentation

Enhance the diversity and richness of your training data through our data augmentation techniques. We generate synthetic samples, perform data synthesis, and apply data augmentation algorithms to expand the size and variety of your dataset.


Privacy and Compliance

We understand the importance of data privacy and compliance. Rest assured that your data will be handled with the utmost confidentiality and in compliance with applicable data protection regulations.

Customization and Flexibility

We tailor our data preparation services to meet your unique needs. Whether you require domain-specific data, specific data formats, or custom preprocessing steps, we work closely with you to deliver a solution that aligns with your objectives.


Collaboration and Support

Our dedicated team of data scientists and engineers collaborate closely with you throughout the data preparation process. We provide guidance, support, and expertise to ensure that your data is prepared to maximize the performance of your LLM.

With our Data Preparation for Fine-tuning LLMs solution, you can accelerate the training process, enhance model performance, and achieve exceptional results in natural language understanding, text generation, sentiment analysis, and more.

Contact us today to learn more about how our data preparation services can empower your LLM projects and take your language models to the next level. Let’s embark on this data-driven journey together!

Access Our Repositories

You can access our Github Repository and Hugging Face Dataset


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