Add README for Micro Llama v0 development

- Added a comprehensive README to describe the project, including an overview of Micro Llama v0, model specifications, file descriptions, and usage instructions.
- Provided installation steps and a sample Python script to load and test the model.
- Included licensing information under Apache 2.0 and details for contributing to the project.

README.md

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 license: apache-2.0
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+
+# Micro Llama v0 (Development)
+
+Micro Llama v0 is a lightweight and experimental version of the LlamaForCausalLM model designed for development and testing purposes. This repository contains the necessary model configuration, tokenizer, and generation settings to run a minimal Llama architecture.
+
+## Model Overview
+
+Micro Llama v0 is based on the LlamaForCausalLM architecture. It is tailored to fit resource-constrained environments for testing the foundational components of a transformer-based language model. This version features:
+
+- **1 hidden layer**
+- **2048 hidden size**
+- **32 attention heads**
+- **5632 intermediate size**
+- **Max position embeddings** of 2048
+- **Vocabulary size** of 32,000
+
+These parameters make the model compact and suitable for development, while still maintaining key characteristics of the Llama architecture.
+
+## Files and Configuration
+
+- **`config.json`**: Contains the model architecture configuration, such as hidden size, number of attention heads, hidden layers, and activation functions.
+- **`generation_config.json`**: Specifies generation parameters, including max length and token behavior.
+- **`model.safetensors`**: Stores the model weights in a safe and efficient format.
+- **`special_tokens_map.json`**: Maps the special tokens used by the model, including `<s>`, `</s>`, `<unk>`, and `</s>` (for padding).
+- **`tokenizer.json`**: Defines the tokenizer configuration, including vocabulary size and token mapping.
+- **`tokenizer_config.json`**: Further configures the tokenizer, specifying token types, maximum sequence length, and other tokenizer options.
+
+## Requirements
+
+- [Transformers](https://github.com/huggingface/transformers) version 4.44.0 or above
+- PyTorch version compatible with the model's `float32` tensor type
+- `safetensors` package for loading model weights
+
+## Usage
+
+1. Clone the repository:
+   ```bash
+   git clone https://github.com/your-repo/micro-llama.git
+   cd micro-llama
+   ```
+2.	Install the required dependencies:
+    ```bash
+    pip install transformers safetensors torch
+    ```
+3.	Load the model in your code:
+    ```python
+    from transformers import LlamaForCausalLM, LlamaTokenizer
+
+    tokenizer = LlamaTokenizer.from_pretrained("UnieAI-Wilson/micro-llama-0-dev")
+    model = LlamaForCausalLM.from_pretrained("UnieAI-Wilson/micro-llama-0-dev", torch_dtype="float16")
+
+    inputs = tokenizer("Your text here", return_tensors="pt")
+    outputs = model.generate(**inputs)
+    print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+    ```
+## License
+Micro Llama v0 is licensed under the Apache 2.0 License. See the LICENSE file for details.
+
+## Contribution
+
+This is an experimental and evolving project. Contributions are welcome, and feel free to submit issues or pull requests.
+
+## Disclaimer
+
+This is an early-stage development version, and the model may undergo significant changes. It is not intended for production use.