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--- |
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base_model: unsloth/gemma-1.1-2b-it-bnb-4bit |
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datasets: |
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- ssbuild/alpaca_flan-muffin |
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language: |
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- en |
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library_name: peft |
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license: apache-2.0 |
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pipeline_tag: text-generation |
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--- |
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# Xenith |
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Welcome to the Xenith Model repository! This model is fine-tuned for advanced text generation tasks, built on top of the unsloth/gemma-1.1-2b-it-bnb-4bit base model, and further enhanced using the ssbuild/alpaca_flan-muffin dataset. The model is designed to provide high-quality and coherent text generation in English. |
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## Introduction |
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The Xenith Model is a powerful text generation model built using the PEFT (Parameter-Efficient Fine-Tuning) library. It leverages the strengths of the unsloth/gemma-1.1-2b-it-bnb-4bit model and is fine-tuned on the ssbuild/alpaca_flan-muffin dataset. Xenith is designed to perform well across a variety of text generation tasks, delivering consistent and high-quality outputs. |
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## Features |
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- Efficient Text Generation: Powered by a 2 billion parameter model optimized for text generation tasks. |
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- Fine-Tuned Performance: Enhanced through fine-tuning on the ssbuild/alpaca_flan-muffin dataset for better contextual understanding and response accuracy. |
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- Compact and Fast: Uses 4-bit quantization for faster inference and lower memory usage without compromising quality. |
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- Open Source: Licensed under the Apache-2.0 license, making it free to use, modify, and distribute. |
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# Model Details |
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- Base Model: unsloth/gemma-1.1-2b-it-bnb-4bit |
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- Fine-tuning Dataset: ssbuild/alpaca_flan-muffin |
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- Language: English |
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- Library: PEFT (Parameter-Efficient Fine-Tuning) |
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- License: Apache-2.0 |
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# Dataset |
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The Xenith Model is fine-tuned using the ssbuild/alpaca_flan-muffin dataset. This dataset is known for its diverse and high-quality examples, making it ideal for training models that require nuanced understanding and contextual accuracy. |
