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@@ -6,7 +6,7 @@ pipeline_tag: text-generation
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- <div align="center"><h1 align="center">~ GenZ ~</h1><img src="https://github.com/BudEcosystem/GenZ/blob/main/assets/genz-logo.png" width=150></div>
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  <p align="center"><i>Democratizing access to LLMs for the open-source community.<br>Let's advance AI, together. </i></p>
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  Welcome to **GenZ**, an advanced Large Language Model (LLM) fine-tuned on the foundation of Meta's open-source Llama V2 13B parameter model. At Bud Ecosystem, we believe in the power of open-source collaboration to drive the advancement of technology at an accelerated pace. Our vision is to democratize access to fine-tuned LLMs, and to that end, we will be releasing a series of models across different parameter counts (7B, 13B, and 70B) and quantizations (32-bit and 4-bit) for the open-source community to use, enhance, and build upon.
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- <p align="center"><img src="https://github.com/BudEcosystem/GenZ/blob/main/assets/MTBench_CompareChart_28July2023.png" width="500"></p>
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  The smaller quantization version of our models makes them more accessible, enabling their use even on personal computers. This opens up a world of possibilities for developers, researchers, and enthusiasts to experiment with these models and contribute to the collective advancement of language model technology.
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- <img src="https://github.com/BudEcosystem/GenZ/blob/main/assets/screenshot_genz13bv2.png" width="100%">
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- | ![Python](https://github.com/BudEcosystem/GenZ/blob/main/assets/Python.gif) | ![Poem](https://github.com/BudEcosystem/GenZ/blob/main/assets/Poem.gif) | ![Email](https://github.com/BudEcosystem/GenZ/blob/main/assets/Email.gif)
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  |:--:|:--:|:--:|
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  | *Code Generation* | *Poem Generation* | *Email Generation* |
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  <!--
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- <p align="center"><img src="https://github.com/adrot-dev/git-test/blob/main/assets/Python.gif" width="33%" alt="Python Code"><img src="https://github.com/adrot-dev/git-test/blob/main/assets/Poem.gif" width="33%"><img src="https://github.com/adrot-dev/git-test/blob/main/assets/Email.gif" width="33%"></p>
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  We're proud to say that our model performs at a level that's close to the Llama-70B-chat model on the MT Bench and top of the list among 13B models.
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- <p align="center"><img src="https://github.com/BudEcosystem/GenZ/blob/main/assets/mt_bench_score.png" width="500"></p>
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  In the transition from GenZ V1 to V2, we noticed some fascinating performance shifts. While we saw a slight dip in coding performance, two other areas, Roleplay and Math, saw noticeable improvements.
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- Check the GitHub for the code -> [GenZ](https://github.com/BudEcosystem/GenZ)
 
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+ <div align="center"><h1 align="center">~ GenZ ~</h1><img src="https://raw.githubusercontent.com/BudEcosystem/GenZ/blob/main/assets/genz-logo.png" width=150></div>
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  <p align="center"><i>Democratizing access to LLMs for the open-source community.<br>Let's advance AI, together. </i></p>
 
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  Welcome to **GenZ**, an advanced Large Language Model (LLM) fine-tuned on the foundation of Meta's open-source Llama V2 13B parameter model. At Bud Ecosystem, we believe in the power of open-source collaboration to drive the advancement of technology at an accelerated pace. Our vision is to democratize access to fine-tuned LLMs, and to that end, we will be releasing a series of models across different parameter counts (7B, 13B, and 70B) and quantizations (32-bit and 4-bit) for the open-source community to use, enhance, and build upon.
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+ <p align="center"><img src="https://raw.githubusercontent.com/BudEcosystem/GenZ/blob/main/assets/MTBench_CompareChart_28July2023.png" width="500"></p>
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  The smaller quantization version of our models makes them more accessible, enabling their use even on personal computers. This opens up a world of possibilities for developers, researchers, and enthusiasts to experiment with these models and contribute to the collective advancement of language model technology.
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+ <img src="https://raw.githubusercontent.com/BudEcosystem/GenZ/blob/main/assets/screenshot_genz13bv2.png" width="100%">
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+ | ![Python](https://raw.githubusercontent.com/BudEcosystem/GenZ/blob/main/assets/Python.gif) | ![Poem](https://raw.githubusercontent.com/BudEcosystem/GenZ/blob/main/assets/Poem.gif) | ![Email](https://raw.githubusercontent.com/BudEcosystem/GenZ/blob/main/assets/Email.gif)
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  |:--:|:--:|:--:|
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  | *Code Generation* | *Poem Generation* | *Email Generation* |
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  <!--
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+ <p align="center"><img src="https://raw.githubusercontent.com/adrot-dev/git-test/blob/main/assets/Python.gif" width="33%" alt="Python Code"><img src="https://raw.githubusercontent.com/adrot-dev/git-test/blob/main/assets/Poem.gif" width="33%"><img src="https://raw.githubusercontent.com/adrot-dev/git-test/blob/main/assets/Email.gif" width="33%"></p>
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  We're proud to say that our model performs at a level that's close to the Llama-70B-chat model on the MT Bench and top of the list among 13B models.
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+ <p align="center"><img src="https://raw.githubusercontent.com/BudEcosystem/GenZ/blob/main/assets/mt_bench_score.png" width="500"></p>
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  In the transition from GenZ V1 to V2, we noticed some fascinating performance shifts. While we saw a slight dip in coding performance, two other areas, Roleplay and Math, saw noticeable improvements.
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+ Check the GitHub for the code -> [GenZ](https://raw.githubusercontent.com/BudEcosystem/GenZ)