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---
license: apache-2.0
language:
- en
library_name: transformers
tags:
- Code Generation
- Logical Reasoning
- Problem Solving
- Text Generation
- AI Programming Assistant
---
<h1>The-Trinity-Coder-7B: 3 Blended Coder Models - Unified Coding Intelligence</h1>
<p><strong>Overview</strong></p>
<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>
<h2>The Blend</h2>
<ul>
<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>
<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>
<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>
</ul>
<h2>Model Synthesis Approach</h2>
<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>
<ul>
<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>
<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>
<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>
</ul>
<h2>Usage and Implementation</h2>
<pre><code>from transformers import AutoTokenizer, AutoModelForCausalLM
model_name = "YourRepository/The-Trinity-Coder-7B"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
prompt = "Your prompt here"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
</code></pre>
<h2>Acknowledgments</h2>
<p>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.</p>
---
base_model: []
library_name: transformers
tags:
- mergekit
- merge
---
# merged_folder
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) 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:
```yaml
base_model: X:/text-generation-webui-main/models/uukuguy_speechless-zephyr-code-functionary-7b
models:
- model: X:/text-generation-webui-main/models/beowolx_CodeNinja-1.0-OpenChat-7B
parameters:
density: 0.5
weight: 0.4
- model: X:/text-generation-webui-main/models/Kukedlc_NeuralExperiment-7b-MagicCoder-v7.5
parameters:
density: 0.5
weight: 0.4
merge_method: ties
parameters:
normalize: true
dtype: float16
``` |