SLMs and LLMs are engineered and trained from the ground up to efficiently run on client devices and edge environments, delivering state-of-the-art performance.
We’ve open-sourced over 20 models, making them available for the community of AI enthusiasts to try.
Our open-source models are used by over 60,000 developers, startups, SMEs, and enterprises.
An advanced Large Language Model (LLM) fine-tuned on the foundation of Meta's open-source Llama V2 70B parameter model.
An advanced multimodal AI model fine-tuned to understand text and visual inputs to provide contextually relevant responses.
The instruction fine tuned model with 4K input length. The model is finetuned on top of pretrained LLaMa2
The instruction finetuned model with 4K input length. The model is finetuned on top of pretrained LLaMa2
An advanced Large Language Model (LLM) fine-tuned on the foundation of Meta's open-source Llama V2 13B parameter model.
The instruction finetuned model with 4K input length. The model is finetuned on top of pretrained LLaMa2
The model is a finetuned version of Genz-13B-v2 with a context size of 16K. The model architecture is updated to have lamda attention.
Bud Millennial Code Gen open-source models are currently the State of the Art (SOTA) for code generation, beating all the existing models of all sizes.
Bud Millennial Code Gen open-source models are currently the State of the Art (SOTA) for code generation, beating all the existing models of all sizes.
Bud Millennial Code Gen open-source models are currently the State of the Art (SOTA) for code generation, beating all the existing models of all sizes.
Bud Millennial Code Gen open-source models are currently the State of the Art (SOTA) for code generation, beating all the existing models of all sizes.
TBud Millennial Code Gen open-source models are currently the State of the Art (SOTA) for code generation, beating all the existing models of all sizes.
This model, with 634 million parameters, was meticulously pre-trained from scratch on a custom synthetic dataset comprising 12 billion tokens.
Our 3.51 billion parameter marvel pretrained from custom synthetic data generated with textbook style.
This 634m parameter model is pre-trained from scratch using a custom synthetic dataset of 5B tokens.
This 1.1B parameter model is pre-trained from scratch using a custom-curated dataset of 41B tokens.
Tansen is a text-to-speech program designed for strong multi-voice capabilities, highly realistic prosody and intonation, and precise speaking rate control.
A Latent Diffusion Model (LDM) fine-tuned on the foundation of StablitiyAI's open-source SDXL model.
Built on CodeLLaMa 13B, our model has been meticulously fine-tuned with a curated dataset comprising 100k SQL query generation instructions, ensuring quality and precision.
Built on Mistral 7B, our model has been meticulously fine-tuned with a curated dataset comprising 100k SQL query generation instructions, ensuring quality and precision.
High performance and accuracy is achieved by using bud’s proprietary training methodology—with custom optimizers, learning functions, and batching techniques.
Bud models are optimized for all devices: 2.8B for client devices, 600M for edge, and 10M, 40M, or 60M for super edge applications.
Bud’s Small language models maintain Cloud LLM like accuracy using Hybrid technology.
With an expanding architecture, bud models deliver high accuracy, maintain statefulness, & easily personalized.
Real time TTFT and Inferencing optimize performance for minimal delay in AI responses.
GenAI Made Practical, Profitable and Scalable!
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