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Devavrat28/peshwai-historian-ai
peshwai-historian-ai is a machine learning model from Devavrat28. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
marathi विषय: नाना फडणवीसांचे गुप्त राजकारण सविस्तर माहिती: marathi नाना फडणवीस हे पेशवाईतील अत्यंत मुत्सद्दी आणि धोरणशक्ती असलेले व्यक्तिमत्व होते. माधवराव पेशव्यांच्या मृत्यूनंतर, सत्तेची रिकामी जागा भरून काढण्यासाठ…
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Updated May 9, 2025
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From the Hugging Face model README
📜 Peshwai Historian AI (Marathi Language Model)
An LLM fine-tuned to answer deep, culturally rich questions about the Peshwa era of Pune — in fluent Marathi.
✨ Overview
`peshwai-historian-ai` is a fine-tuned language model focused on the **Maratha Peshwa dynasty, trained on **curated historical text in Marathi. The model can answer questions about lesser-known events, policies, and figures from the 18th-century Pune region with contextual, factual, and culturally accurate responses — especially useful for educators, students, historians, and heritage lovers.
🔍 What Makes It Special?
📖 Marathi-native output: Generates grammatically rich and natural Marathi text
🕰️ Historical awareness: Avoids commonly known facts (like Bajirao, Shaniwarwada) and focuses on underrepresented topics
🧠 Fine-tuned on real historical documents: Including rare facts about Nana Phadnavis, Mahadji Shinde, diplomacy, cultural shifts, etc.
🗣️ Few-shot prompting optimized: Learns from examples to improve answer quality
🧠 Example Prompt
```marathi
विषय: नाना फडणवीसांचे गुप्त राजकारण
सविस्तर माहिती:
नाना फडणवीस हे पेशवाईतील अत्यंत मुत्सद्दी आणि धोरणशक्ती असलेले व्यक्तिमत्व होते. माधवराव पेशव्यांच्या मृत्यूनंतर, सत्तेची रिकामी जागा भरून काढण्यासाठी त्यांनी 'बारभाई मंडळ' तयार केले...
from unsloth import FastLanguageModel
import torch
model, tokenizer = FastLanguageModel.from_pretrained(
model_name = "Devavrat28/peshwai-historian-ai", # replace with your HF username
max_seq_length = 4096,
dtype = torch.float16,
load_in_4bit = True
)
FastLanguageModel.for_inference(model)
prompt = "विषय: माधवराव पेशव्यांचा आरोग्यावर झालेला परिणाम\nसविस्तर माहिती:"
inputs = tokenizer([prompt], return_tensors="pt").to("cuda")
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
| Setting | Value |
|---|---|
| Base Model | Gemma / LLaMA / Open LLM |
| Fine-tuning Method | Supervised Fine-Tuning (SFT) |
| Framework | Unsloth + 🤗 TRL |
| Dataset | Marathi historical text (~50K tokens) |
| Technique | Continued pretraining + SFT |
| Language | मराठी (Marathi) |
If you use this model in research or production, please consider citing:
@misc{peshwaiHistorian2024,
title={Peshwai Historian AI: A Marathi LLM for Regional Heritage},
author={Devavrat Samak},
year={2024},
howpublished={\url{https://huggingface.co/devavrat/peshwai-historian-ai}},
}
Developed by Devavrat Samak
Inspired by the rich cultural heritage of Pune and the legacy of the Peshwas.
I welcome pull requests, prompts, dataset contributions, and collaborations. Reach out via Hugging Face or GitHub.