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DeeperML
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Together AI and Agentica have announced the release of DeepCoder-14B, an open-source AI coding model designed to compete with proprietary alternatives like OpenAI's o3-mini and o1. Built upon the DeepSeek-R1 architecture, DeepCoder-14B aims to provide developers with a transparent and fully controllable solution for code generation and reasoning tasks. The release is significant as it offers a robust open-source option in a domain often dominated by closed-source models, giving researchers and developers more flexibility and control over their AI coding tools.
DeepCoder-14B has demonstrated strong performance across several challenging coding benchmarks, achieving results comparable to o3-mini and o1 while utilizing only 14 billion parameters. This smaller footprint makes it potentially more efficient to run than many larger models. Notably, the model shows improved mathematical reasoning skills, scoring 73.8% on the AIME 2024 benchmark, a 4.1% improvement over its base model, indicating that reasoning skills learned through coding tasks can generalize to other domains. The training process involved overcoming challenges in curating high-quality training data by implementing a strict pipeline to filter examples for validity, complexity, and duplication.
The success of DeepCoder-14B is attributed to innovations in training data curation and reward function design. The team meticulously gathered and filtered examples from various datasets to create a high-quality dataset of 24,000 problems. A straightforward reward function was implemented, providing a positive signal only when the generated code passed all unit tests within a specified time limit. The teams have fully open-sourced the model, its training data, code, logs and system optimizations, which can help researchers improve their work and accelerate progress, fostering further advancements in the field of AI-driven code generation.
References :
DeepCoder-14B has demonstrated strong performance across several challenging coding benchmarks, achieving results comparable to o3-mini and o1 while utilizing only 14 billion parameters. This smaller footprint makes it potentially more efficient to run than many larger models. Notably, the model shows improved mathematical reasoning skills, scoring 73.8% on the AIME 2024 benchmark, a 4.1% improvement over its base model, indicating that reasoning skills learned through coding tasks can generalize to other domains. The training process involved overcoming challenges in curating high-quality training data by implementing a strict pipeline to filter examples for validity, complexity, and duplication.
The success of DeepCoder-14B is attributed to innovations in training data curation and reward function design. The team meticulously gathered and filtered examples from various datasets to create a high-quality dataset of 24,000 problems. A straightforward reward function was implemented, providing a positive signal only when the generated code passed all unit tests within a specified time limit. The teams have fully open-sourced the model, its training data, code, logs and system optimizations, which can help researchers improve their work and accelerate progress, fostering further advancements in the field of AI-driven code generation.
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References :
- the-decoder.com: DeepCoder-14B matches OpenAI's o3-mini performance with a smaller footprint
- AI News | VentureBeat: DeepCoder delivers top coding performance in efficient 14B open model
- www.analyticsvidhya.com: DeepCoder-14B: The Open-Source Competition to o3-mini and o1
- www.marktechpost.com: Together AI Released DeepCoder-14B-Preview: A Fully Open-Source Code Reasoning Model That Rivals o3-Mini With Just 14B Parameters
- THE DECODER: DeepCoder-14B matches OpenAI's o3-mini performance with a smaller footprint
- Analytics Vidhya: DeepCoder-14B: The Open-Source Competition to o3-mini and o1
- MarkTechPost: Together AI Released DeepCoder-14B-Preview: A Fully Open-Source Code Reasoning Model That Rivals o3-Mini With Just 14B Parameters
Classification:
- HashTags: #DeepCoder #OpenSourceAI #AICoding
- Company: Together AI
- Target: Developers
- Product: DeepCoder-14B
- Feature: Open-Source AI Coding Model
- Type: AI
- Severity: Informative