Upload README.md

README.md

@@ -1,6 +1,6 @@
-# Linformer-based Language Model Inference on Hugging Face
+# Linformer-based Language Model Inference
 
-This repository provides the code and configuration needed to use the Linformer-based language model hosted on Hugging Face under the model ID `anto18671/lumenspark`. The model is designed for efficient inference, leveraging the Linformer architecture to handle long sequences with reduced memory and computational overhead.
+This repository provides the code and configuration needed to use the Linformer-based language model, designed for efficient inference, leveraging the Linformer architecture to handle long sequences with reduced memory and computational overhead.
 
 ## Table of Contents
 
@@ -13,11 +13,11 @@ This repository provides the code and configuration needed to use the Linformer-
 
 ## Introduction
 
-This project provides the necessary setup and guidance to perform text generation using the Linformer-based language model, optimized for fast and efficient inference. The model is hosted on Hugging Face and can be loaded directly for tasks like text generation, completion, and other language modeling tasks.
+This project provides the necessary setup and guidance to perform text generation using the Linformer-based language model, optimized for fast and efficient inference. The model can be loaded for tasks like text generation, completion, and other language modeling tasks.
 
 The model has been trained on large datasets like OpenWebText and BookCorpus, but this repository focuses on inference, allowing you to generate text quickly with minimal resource consumption.
 
-**Note**: This model uses a custom attention mechanism based on Linformer, which is not supported by Hugging Face's `AutoModel` API. Therefore, you must use the provided `LumensparkModel` and `LumensparkConfig` to load the model, as described below.
+**Note**: This model uses a custom attention mechanism based on Linformer. Therefore, you must use the provided `LumensparkModel` and `LumensparkConfig` to load the model.
 
 ## Model Architecture
 
@@ -46,18 +46,28 @@ These parameters can be adjusted during inference to control the nature of the g
 
 ## Usage
 
-You can easily load the model and perform inference using Hugging Face's Transformers library. However, as this model uses Linformer-based attention, you **cannot** use the `AutoModel` APIs. Instead, the `LumensparkModel` and `LumensparkConfig` must be loaded, as shown in the following example:
+You can easily load the model and perform inference by installing the architecture via pip. Since this model uses Linformer-based attention, you **must** install the custom package and load the `LumensparkModel` and `LumensparkConfig`, as shown in the following example:
+
+### Installation
+
+First, install the package:
+
+```bash
+pip install lumenspark
+```
+
+### Inference Example
 
 ```python
 from lumenspark import LumensparkConfig, LumensparkModel
 from transformers import AutoTokenizer
 
-# Load the configuration and model from Hugging Face
-config = LumensparkConfig.from_pretrained("anto18671/lumenspark")
-model = LumensparkModel.from_pretrained("anto18671/lumenspark", config=config)
+# Load the configuration and model
+config = LumensparkConfig.from_pretrained("path/to/your/model/config")
+model = LumensparkModel.from_pretrained("path/to/your/model", config=config)
 
 # Load the tokenizer
-tokenizer = AutoTokenizer.from_pretrained("anto18671/lumenspark")
+tokenizer = AutoTokenizer.from_pretrained("path/to/your/tokenizer")
 
 # Example input text
 input_text = "Once upon a time"