Create README.md

README.md

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+---
+base_model: unsloth/gemma-1.1-2b-it-bnb-4bit
+datasets:
+  - ssbuild/alpaca_flan-muffin
+language:
+  - en
+library_name: peft
+license: apache-2.0
+pipeline_tag: text-generation
+---
+
+# Xenith
+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.
+
+## Introduction
+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.
+
+## Features
+- Efficient Text Generation: Powered by a 2 billion parameter model optimized for text generation tasks.
+- Fine-Tuned Performance: Enhanced through fine-tuning on the ssbuild/alpaca_flan-muffin dataset for better contextual understanding and response accuracy.
+- Compact and Fast: Uses 4-bit quantization for faster inference and lower memory usage without compromising quality.
+- Open Source: Licensed under the Apache-2.0 license, making it free to use, modify, and distribute.
+
+# Model Details
+- Base Model: unsloth/gemma-1.1-2b-it-bnb-4bit
+- Fine-tuning Dataset: ssbuild/alpaca_flan-muffin
+- Language: English
+- Library: PEFT (Parameter-Efficient Fine-Tuning)
+- License: Apache-2.0
+
+# Dataset
+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.