Create README.md

README.md

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+---
+base_model: microsoft/Phi-3-mini-4k-instruct
+datasets:
+  - AlignmentLab-AI/alpaca-cot-collection
+language:
+  - en
+library_name: peft
+license: apache-2.0
+pipeline_tag: text-generation
+---
+
+# Xenith-3B
+Xenith-3B is a fine-tuned language model based on the microsoft/Phi-3-mini-4k-instruct model. It has been specifically trained on the AlignmentLab-AI/alpaca-cot-collection dataset, which focuses on chain-of-thought reasoning and instruction following.
+
+# Model Overview
+- Model Name: Xenith-3B
+- Base Model: microsoft/Phi-3-mini-4k-instruct
+- Fine-Tuned On: AlignmentLab-AI/alpaca-cot-collection
+- Model Size: 3 Billion parameters
+- Architecture: Transformer-based LLM
+
+# Training Details
+- Objective: Fine-tune the base model to enhance its performance on tasks requiring complex reasoning and multi-step problem-solving.
+- Training Duration: 10 epochs
+- Batch Size: 8
+- Learning Rate: 3e-5
+- Optimizer: AdamW
+- Hardware Used: 2x NVIDIA L4 GPUs
+
+# Performance
+Xenith-3B excels in tasks that require:
+
+- Chain-of-thought reasoning
+- Instruction following
+- Contextual understanding
+- Complex problem-solving
+- 
+The model has shown significant improvements in these areas compared to the base model.