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README.md
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/6405c7afbe1a9448a79b177f/hZkh-FJITEKdX32gn0cu-.png)
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<p><strong>Overview</strong></p>
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<p>The-Trinity-Coder-7B derives from the fusion of three distinct AI models, each specializing in unique aspects of coding and programming challenges. This model unifies the capabilities of
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<h2>The Blend</h2>
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<ul>
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<li><strong>Comprehensive Coding Knowledge:</strong> TrinityAI combines
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<li><strong>Advanced Code Completion:</strong> With its extensive context window, TrinityAI excels in project-level code completion, offering suggestions that are contextually relevant and syntactically accurate.</li>
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<li><strong>Specialized Skills Integration:</strong> The-Trinity-Coder provides code completion but is also good at logical reasoning for its size, mathematical problem-solving, and understanding complex programming concepts.</li>
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</ul>
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<h2>Model Synthesis Approach</h2>
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<p>The blending of the three models into TrinityAI utilized a unique merging technique that focused on preserving the core strengths of each component model:</p>
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<ul>
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<li><strong>
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<li><strong>NeuralExperiment-7b-MagicCoder:</strong> Trained on datasets focusing on logical reasoning, mathematics, and programming, this model enhances TrinityAI's problem-solving and logical reasoning capabilities.</li>
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<li><strong>Speechless-Zephyr-Code-Functionary-7B:</strong> Part of the Moloras experiments, this model contributes enhanced coding proficiency and dynamic skill integration through its unique LoRA modules.</li>
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</ul>
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/6405c7afbe1a9448a79b177f/hZkh-FJITEKdX32gn0cu-.png)
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<p><strong>Overview</strong></p>
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<p>The-Trinity-Coder-7B derives from the fusion of three distinct AI models, each specializing in unique aspects of coding and programming challenges. This model unifies the capabilities of beowolx_CodeNinja-1.0-OpenChat-7B, NeuralExperiment-7b-MagicCoder, and Speechless-Zephyr-Code-Functionary-7B, creating a versatile and powerful new blended model. The integration of these models was achieved through a merging technique, in order to harmonize their strengths and mitigate their individual weaknesses.</p>
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<h2>The Blend</h2>
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<ul>
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<li><strong>Comprehensive Coding Knowledge:</strong> TrinityAI combines knowledge of coding instructions across a wide array of programming languages, including Python, C, C++, Rust, Java, JavaScript, and more, making it a versatile assistant for coding projects of any scale.</li>
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<li><strong>Advanced Code Completion:</strong> With its extensive context window, TrinityAI excels in project-level code completion, offering suggestions that are contextually relevant and syntactically accurate.</li>
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<li><strong>Specialized Skills Integration:</strong> The-Trinity-Coder provides code completion but is also good at logical reasoning for its size, mathematical problem-solving, and understanding complex programming concepts.</li>
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</ul>
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<h2>Model Synthesis Approach</h2>
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<p>The blending of the three models into TrinityAI utilized a unique merging technique that focused on preserving the core strengths of each component model:</p>
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<ul>
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<li><strong>beowolx_CodeNinja-1.0-OpenChat-7B:</strong> This model brings an expansive database of coding instructions, refined through Supervised Fine Tuning, making it an advanced coding assistant.</li>
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<li><strong>NeuralExperiment-7b-MagicCoder:</strong> Trained on datasets focusing on logical reasoning, mathematics, and programming, this model enhances TrinityAI's problem-solving and logical reasoning capabilities.</li>
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<li><strong>Speechless-Zephyr-Code-Functionary-7B:</strong> Part of the Moloras experiments, this model contributes enhanced coding proficiency and dynamic skill integration through its unique LoRA modules.</li>
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</ul>
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