Akjindal53244
Models by this creator
📶
Llama-3.1-Storm-8B
151
The Llama-3.1-Storm-8B model was developed by akjindal53244 and their team. This model outperforms the Meta AI Llama-3.1-8B-Instruct and Hermes-3-Llama-3.1-8B models across diverse benchmarks. The approach involves self-curation, targeted fine-tuning, and model merging. Model inputs and outputs Inputs Text**: The Llama-3.1-Storm-8B model takes in text as input. Outputs Text and code**: The model generates text and code as output. Capabilities The Llama-3.1-Storm-8B model demonstrates significant improvements over existing Llama models across a range of benchmarks, including instruction-following, knowledge-driven QA, reasoning, truthful answer generation, and function calling. What can I use it for? The Llama-3.1-Storm-8B model can be used for a variety of natural language generation tasks, such as chatbots, code generation, and question answering. Its strong performance on instruction-following and knowledge-driven tasks makes it a powerful tool for developing intelligent assistants and automation systems. Things to try Developers can experiment with using the Llama-3.1-Storm-8B model as a foundation for building more specialized language models or integrating it into larger AI systems. Its improved capabilities across a wide range of benchmarks suggest it could be a valuable resource for a variety of real-world applications.
Updated 9/19/2024
🌿
Arithmo-Mistral-7B
59
The Arithmo-Mistral-7B model is a fine-tuned version of the powerful Mistral-7B model, developed by Ashvini Kumar Jindal and Ankur Parikh. This model exhibits strong mathematical reasoning capabilities, outperforming existing 7B and 13B state-of-the-art mathematical reasoning models on the GSM8K and MATH benchmarks. In comparison, the MetaMath-Mistral-7B model is another fine-tuned Mistral-7B that focuses on the MetaMathQA dataset, achieving impressive results on mathematical reasoning tasks. Both the Arithmo-Mistral-7B and MetaMath-Mistral-7B models leverage the capabilities of the base Mistral-7B model to excel at mathematical problem-solving. Model inputs and outputs The Arithmo-Mistral-7B model is a text-to-text model, taking in mathematical questions or prompts as input and generating responses that reason through the problem and provide the answer. Inputs Mathematical word problems or questions expressed in natural language Outputs Step-by-step reasoning to solve the mathematical problem The final answer to the question In some cases, the model can also generate a Python program that, when executed, provides the answer to the problem Capabilities The Arithmo-Mistral-7B model demonstrates strong mathematical reasoning abilities, outperforming existing 7B and 13B models on the GSM8K and MATH benchmarks. It can tackle a wide range of mathematical problems, from arithmetic to algebra to geometry, and provide detailed reasoning and solutions. The model can also generate Python code to solve mathematical problems, showcasing its versatility and programming skills. What can I use it for? The Arithmo-Mistral-7B model can be a valuable tool for students, educators, and researchers working on mathematical problems and reasoning. It can be used to aid in homework and exam preparation, to generate practice problems, or to provide step-by-step explanations for complex mathematical concepts. Additionally, the model's ability to generate Python code could be leveraged in programming and computer science education, or in the development of mathematical tools and applications. Things to try One interesting aspect of the Arithmo-Mistral-7B model is its ability to not only solve mathematical problems, but to also provide step-by-step reasoning and generate Python code to solve the problems. Try prompting the model with a variety of mathematical word problems and observe how it tackles the problems, generates the reasoning, and produces the final answer. Experiment with different problem types and complexities to see the full extent of the model's capabilities.
Updated 5/28/2024