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## 🕊️ 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
---
### 📂 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.
---
### 🎯 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
---
### 💬 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))
```
---
### 🚫 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.
---
### 🌏 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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