The yDataPrep package simplifies the process of preparing datasets for fine-tuning or training various large language models available in the Hugging Face Transformers library. Whether you're using a model from the Hugging Face repository or have your own dataset, this package streamlines the data integration for a seamless training experience.
The yInference utility optimizes model inference, enabling users to evaluate their trained or fine-tuned models prior to Hugging Face Hub deployment. This Python package guarantees dependable model assessment within your workflow, elevating model efficacy and deployment assurance.
We offer tailored fine-tuning services for language models, ranging from Xm to Yb in size, to optimize your specific use cases. Our expertise enhances your workflow, ensuring the perfect model fit for your needs.
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Empowering companies with tools like yDataPrep and yInference to fine-tune Large Language Models for their specific use cases.
The yDataPrep package facilitates the streamlined preparation of datasets for the purpose of fine-tuning or training large language models found in the Hugging Face Transformers library. Whether you are utilizing a model sourced from the Hugging Face repository or possess a custom dataset, this package enhances the data integration process to ensure a smooth and efficient training experience.
Learn MoreThe yInference tool streamlines model inference, allowing users to assess their trained or fine-tuned models before deploying them to the Hugging Face Hub. This python package ensures reliable model evaluation within your workflow, enhancing model performance and deployment confidence.
Learn MoreOur comprehensive suite of services specializes in custom fine-tuning for language models, spanning a vast spectrum from 70m (million) to 7b (billion) in scale. Our dedicated approach ensures a perfect model fit for your unique use cases, significantly enhancing your workflow efficiency and overall outcomes
Learn MoreyService customizes language models from 70m to 7b parameter scale, enhancing your workflow for specific, optimal outcomes.
