Bharat Tiny LLM

--- license: apache-2.0 language: - hi - en - hne tags: - hinglish - hindi - indian-languages - edge-ai - small-language-model - on-device-ai - apple-silicon - mlx - lora - qwen - qwen2 - bharat - indic-nlp - low-resource - conversational - text-generation - offline - lightweight - android base_model: Qwen/Qwen2.5-1.5B library_name: mlx pipeline_tag: text-generation datasets: - ankitdhiman/hinglish-conversations - NebulaByte/IndicInstruct - smangrul/code-py-alpaca thumbnail: https://huggingface.co/eulogik/Bharat-Tiny-LLM/resolve/main/thumbnail.png inference: false --- # 🇮🇳 Bharat-Tiny-LLM <p align="center"> <b>India's first native edge AI for Hinglish & Hindi — running fully offline on ₹8,000 phones.</b><br> <i>A 1.5B-parameter, LoRA-fine-tuned model that speaks fluent Hinglish (Romanized Hindi) <b>and</b> Devanagari Hindi, entirely on-device.</i> </p> <p align="center"> <a href="https://huggingface.co/eulogik/Bharat-Tiny-LLM"><img alt="MLX" src="https://img.shields.io/badge/MLX-4--bit-ff6f00"></a> <a href="https://pypi.org/project/bharat-tiny-llm/"><img alt="PyPI" src="https://img.shields.io/badge/PyPI-bharat--tiny--llm-3776ab"></a> <a href="https://github.com/eulogik/Bharat-Tiny-LLM"><img alt="GitHub" src="https://img.shields.io/badge/GitHub-eulogik%2FBharat--Tiny--LLM-181717"></a> <a href="https://huggingface.co/spaces/eulogik/Bharat-Tiny-LLM"><img alt="Demo" src="https://img.shields.io/badge/%F0%9F%9A%80%20Demo-HF%20Space-8b5cf6"></a> <a href="https://eulogik.com"><img alt="Built by eulogik" src="https://img.shields.io/badge/Built%20by-eulogik-00b894"></a> <a href="https://huggingface.co/eulogik/Bharat-Tiny-LLM/blob/main/LICENSE"><img alt="License" src="https://img.shields.io/badge/License-Apache%202.0-blue.svg"></a> </p> --- ## ✨ Why Bharat-Tiny-LLM? Most Indian-language models do **one** script. Bharat-Tiny-LLM does **both** — and does it on hardware that costs less than a pair of shoes. - 🌐 **Truly bilingual** — Hinglish *and* Devanagari Hindi from a single 1.5B model. - 📱 **Edge-native** — an **880 MB 4-bit MLX build** runs offline on ₹8,000 Android phones & Apple Silicon. No API, no cloud, no internet. - 🪶 **Small but real** — 1.5B params, ~57 tok/s on a Mac Mini M4. - 💸 **$0 training cost** — fine-tuned on a Mac Mini M4, zero cloud compute. - 🆓 **Open weights** — Apache-2.0, self-hostable, no vendor...