## 🕊️ TagoreX – A Bengali Text Generator Inspired by Tagore

**Model name:** `SwastikGuhaRoy/TagoreX`
**Base model:** `GPT-2` with LoRA adapters [(based on `AddaGPT2.0`)](https://huggingface.co/SwastikGuhaRoy/AddaGPT2.0)
**Language:** Bengali
**Author:** Swastik Guha Roy (`@SwastikGuhaRoy`)
**License:** MIT
**Model size:** \~124M parameters
**Trained on:** Curated (but imperfect) corpus of Rabindranath Tagore’s writings
**Intended use:** Poetic and philosophical Bengali text generation
**Demo app:** [TagoreX + Gemini Streamlit App](https://tagorexgemini.streamlit.app)

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### 📘 Model Description

**TagoreX** is a fine-tuned version of `AddaGPT2.0` — a small GPT-2 model adapted for Bengali using LoRA (Low-Rank Adaptation).
This model was trained on literary works of Rabindranath Tagore  as a tribute.

The model continues a given Bengali prompt in a Tagore-like poetic tone. It generates \~256 tokens, which are then optionally refined by Gemini AI in a downstream application.

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### 🔧 Technical Details

* **Architecture**: GPT-2 (117M parameters)
* **Training strategy**: Full fine-tuning
* **Epochs**: 22 (symbolically referencing “২২শে শ্রাবণ”)
* **Max sequence length**: 256 tokens
* **Tokenizer**: AutoTokenizer from the base model
* **Framework**: PyTorch + Transformers

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### 📂 Training Data

The dataset includes poems,  prose and other works from Rabindranath Tagore which is [publicly available](https://archive.org/details/RABINDRARACHANABALI/). [The dataset can be accessed in a consolidated .txt format from here](https://huggingface.co/datasets/SwastikGuhaRoy/WorksofTagore) 

⚠️ **Note**: The data may and DOES contain:

* Typos, formatting errors
* OCR issues
* Incomplete or duplicated lines

This model is not a scholarly curation, but an experimental artistic rendering.

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### 🎯 Intended Use

**You can use this model to:**

* Experiment with Bengali poetic text generation
* Create creative writing prompts in Bengali
* Explore Indic LLM capabilities in low-resource settings

This model is **not suitable** for:

* Any commercial or sensitive deployment
* Factual or linguistic accuracy tasks
* Scholarly representation of Tagore’s works

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### 💬 How to Prompt

```python
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("SwastikGuhaRoy/TagoreX")
model = AutoModelForCausalLM.from_pretrained("SwastikGuhaRoy/TagoreX")

prompt = "তুমি রবে নীরবে"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=256, do_sample=True, temperature=0.7)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

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### 🚫 Limitations & Disclaimer

* Not aligned, filtered, or safety-trained.
* Most outputs may be incoherent, repetitive, or nonsensical.
* This is **not** meant to reproduce or replace Tagore's literary work.
* The generation reflects training data and randomness — not any human author.

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### 🌏 Why It Matters

TagoreX demonstrates how even small-scale, open models can express poetic and cultural essence in Indic languages — using limited compute and a lot of curiosity.

It aims to inspire communities to build **Indic LLMs**, especially in low-resource and rural settings.

> *"AI doesn’t have to be massive. It can be local, soulful, and deeply human."*

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### 📫 Contact

📧 Email: `swastikguharoy@googlemail.com`
💬 Feedback, bugs, or nice generations? I'd love to hear from you!

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