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.
The Blend
Comprehensive Coding Knowledge: 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.
Advanced Code Completion: With its extensive context window, TrinityAI excels in project-level code completion, offering suggestions that are contextually relevant and syntactically accurate.
Specialized Skills Integration: The-Trinity-Coder provides code completion but is also good at logical reasoning for its size, mathematical problem-solving, and understanding complex programming concepts.
Model Synthesis Approach
The blending of the three models into TrinityAI utilized a unique merging technique that focused on preserving the core strengths of each component model:
beowolx_CodeNinja-1.0-OpenChat-7B: This model brings an expansive database of coding instructions, refined through Supervised Fine Tuning, making it an advanced coding assistant.
NeuralExperiment-7b-MagicCoder: Trained on datasets focusing on logical reasoning, mathematics, and programming, this model enhances TrinityAI's problem-solving and logical reasoning capabilities.
Speechless-Zephyr-Code-Functionary-7B: Part of the Moloras experiments, this model contributes enhanced coding proficiency and dynamic skill integration through its unique LoRA modules.
Usage and Implementation
from transformers import AutoTokenizer, AutoModelForCausalLM
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Special thanks to the creators and contributors of CodeNinja, NeuralExperiment-7b-MagicCoder, and Speechless-Zephyr-Code-Functionary-7B for providing the base models for blending.
base_model: []
library_name: transformers
tags:
mergekit
merge
merged_folder
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the TIES merge method using uukuguy_speechless-zephyr-code-functionary-7b as a base.
Models Merged
The following models were included in the merge:
*uukuguy_speechless-zephyr-code-functionary-7b
Kukedlc_NeuralExperiment-7b-MagicCoder-v7.5
beowolx_CodeNinja-1.0-OpenChat-7B
Configuration
The following YAML configuration was used to produce this model:
