Update README.md

README.md

@@ -1,3 +1,71 @@
----
-license: mit
----
+---
+license: mit
+datasets:
+- wikimedia/wikipedia
+language:
+- en
+metrics:
+- bleu
+- rouge
+library_name: adapter-transformers
+pipeline_tag: reinforcement-learning
+tags:
+- code
+---
+# Super Large Language Model
+
+This project implements a super-large language model using PyTorch. The model architecture is based on the Transformer model.
+
+## Files
+
+- `super_large_language_model.py`: Contains the model architecture.
+- `train.py`: Contains the training script.
+
+## Requirements
+
+- Python 3.7+
+- PyTorch 1.6+
+- NumPy
+
+## Installation
+
+1. Clone the repository:
+    ```bash
+    git clone https://github.com/yourusername/super-large-language-model.git
+    cd super-large-language-model
+    ```
+
+2. Install the required packages:
+    ```bash
+    pip install torch numpy
+    ```
+
+## Usage
+
+1. Prepare your dataset and vocabulary.
+
+2. Run the training script:
+    ```bash
+    python train.py
+    ```
+
+## Model Architecture
+
+**Type**: Transformer
+
+**Style**: Encoder-Decoder
+
+The model is a Transformer-based language model. It consists of:
+
+- An embedding layer for converting input tokens to vectors.
+- Positional encoding to inject information about the position of tokens.
+- A series of Transformer layers.
+- A final linear layer for outputting the predictions.
+
+## Training
+
+The training script trains the model on a dataset of texts. The dataset should be a list of strings, and the vocabulary should be a dictionary mapping characters to indices.
+
+## License
+
+This project is licensed under the MIT License.