Update README.md

README.md

@@ -7,4 +7,77 @@ tags:
 
 This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
 - Library: https://huggingface.co/Aananda-giri/GPT2-Nepali/
-- Docs: [More Information Needed]
+- Docs: [More Information Needed]
+
+---
+
+# GPT-2-Nepali-512 Model
+* 512 represents context length
+
+* This repository contains a custom GPT-2 model trained on Nepali text. Follow the instructions below to use this model for text generation.
+
+---
+
+## How to Use the Model
+
+1. **Download the Required Code**  
+   Save the [`model_code.py`](https://github.com/Aananda-giri/llm.np/blob/main/3.%20GPT-2/sebastian_gutenberg/huggingface_hub/model_code.py) file in the same directory where you'll run the script.
+
+2. **Install Required Libraries**  
+   Ensure you have the necessary libraries installed:  
+   ```bash
+   pip install transformers torch
+   ```
+
+3. **Run the Following Code**  
+   Here's an example to load the model and generate text:
+
+   ```python
+   import torch
+   from model_code import GPTModel, generate_and_print_sample
+   from transformers import PreTrainedTokenizerFast
+
+   # Load the tokenizer
+   tokenizer = PreTrainedTokenizerFast.from_pretrained("Aananda-giri/NepaliBPE")
+
+   # Define the starting text
+   start_context = "रामले भात"
+
+   # Load the pre-trained model
+   loaded_model = GPTModel.from_pretrained("Aananda-giri/GPT2-Nepali")
+
+   # Move the model to the appropriate device (CPU or GPU)
+   device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+   loaded_model.to(device)
+
+   # Generate text
+   generate_and_print_sample(
+       loaded_model, tokenizer, device, start_context
+   )
+   ```
+
+---
+
+## Additional Notes
+
+- **Tokenizer**: The model uses a pre-trained tokenizer available at `Aananda-giri/NepaliBPE`. Ensure this is downloaded and accessible during runtime.
+- **Dependencies**: This code requires `transformers` (by Hugging Face) and `torch` (PyTorch). Install them if not already installed.
+- **Device Compatibility**: The script automatically detects if a CUDA-enabled GPU is available and utilizes it for faster inference. If not, it defaults to the CPU.
+
+---
+
+## Example Output
+
+Input:
+```
+रामले भात
+```
+
+Generated Text:
+```
+रामले भात खाएर सन्तोष माने। ऊ आफ्ना साथीहरूसँग रमाइलो गरिरहेको थियो।
+```
+
+---
+
+Let me know if you'd like further assistance!