🇮🇳 Bharat-Tiny-LLM — Edge AI for Hindi & Hinglish

33.8% Hindi token compression via Brahmi vocabulary injection. Runs offline on Apple Silicon.

bharat-tiny-llm is the official Python package for Bharat-Tiny-LLM v2: a 1.5B-parameter LLM fine-tuned for Hinglish and Devanagari Hindi, with 33.8% token compression achieved via Brahmi script injection — 300 Devanagari subwords injected into Qwen2.5's tokenizer.

Built by eulogik — an India-first AI lab shipping edge AI.

✨ v0.2.0 — Brahmi Token Injection

Install

# Apple Silicon (recommended — MLX, fastest)
pip install bharat-tiny-llm[mlx]

# Other platforms (CPU / CUDA, transformers)
pip install bharat-tiny-llm[torch]

Quick start

v2 model (recommended)

from bharat_tiny_llm import chat

# Uses the v2 MLX model with LoRA adapter
reply = chat(
    [{"role": "user", "content": "कितने बजे मिलना है?"}],
    use_v2=True,
    adapter_path="eulogik/Bharat-Tiny-LLM-v2-MLX/lora_adapter",
)
print(reply)

v1 model (legacy)

from bharat_tiny_llm import chat

reply = chat([{"role": "user", "content": "Chai peete hain?"}])
print(reply)

Low-level MLX

from bharat_tiny_llm import load
from mlx_lm import generate

model, tokenizer = load(use_v2=True)
prompt = tokenizer.apply_chat_template(
    [{"role": "user", "content": "नमस्ते, आप कैसे हैं?"}],
    tokenize=False, add_generation_prompt=True,
)
print(generate(model, tokenizer, prompt=prompt, max_tokens=128))

Model variants

License

Apache-2.0

Links

• 🤗 Model: https://huggingface.co/eulogik/Bharat-Tiny-LLM-v2-MLX
• 💻 Source: https://github.com/eulogik/Bharat-Tiny-LLM
• 🏢 Built by eulogik