Pansophic

Models by this creator

🔍

rocket-3B

pansophic

Total Score

74

rocket-3B is a 3 billion parameter large language model developed by pansophic that was trained on a mix of publicly available datasets using Direct Preference Optimization (DPO). This model sets a new standard for 3B parameter models, outperforming several much larger models on key benchmarks. For example, rocket-3B achieves a higher MT-Bench score than the 65B parameter Guanaco model, and an Alpaca Eval win rate of 79.75%, comparable to the 33B Vicuna v1.3 model. This impressive performance in a compact 3B model is due to the DPO training approach and the use of the ChatML prompt format. Model inputs and outputs rocket-3B is a text-to-text model that can be used for a variety of natural language processing tasks. It takes prompts in the ChatML format as input and generates text responses. Inputs Prompt**: A prompt in the ChatML format, e.g. List 3 synonyms for the word "tiny" Outputs Generated text**: The model's response to the input prompt, e.g. 1. Dwarf\n2. Little\n3. Petite Capabilities rocket-3B demonstrates strong performance on a range of natural language tasks, including question answering, summarization, and language generation. Its compact size and efficient design make it a powerful tool for applications that require fast and accurate language processing without the need for large, resource-intensive models. What can I use it for? rocket-3B can be used as a foundation model for a variety of NLP applications, such as chatbots, virtual assistants, and content generation. Its versatility and strong performance make it a compelling choice for developers and researchers looking to leverage the capabilities of large language models in their projects. Things to try One interesting aspect of rocket-3B is its ability to generate long-form, coherent text. Try providing the model with a prompt that requires a detailed, multi-paragraph response, and observe how it is able to maintain context and flow over an extended sequence. This can be a useful feature for applications that require in-depth explanations or narratives.

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Updated 5/17/2024