Text Generation
MLX
Safetensors
Hindi
English
mistral
ayurveda
hindi
indic
lora
domain-adaptation
sarvam
conversational
4-bit precision
Instructions to use iamarvind/ayurveda-helper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use iamarvind/ayurveda-helper with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("iamarvind/ayurveda-helper") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use iamarvind/ayurveda-helper with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "iamarvind/ayurveda-helper"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "iamarvind/ayurveda-helper" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "iamarvind/ayurveda-helper", "messages": [ {"role": "user", "content": "Hello"} ] }' - Atomic Chat
Ayurveda Helper
Sarvam-M (24B) adapted to Ayurveda in Hindi and English with LoRA domain-adaptive pretraining, trained on a single MacBook Pro (M4 Pro, 48 GB) with MLX. This repo contains the full fused 4-bit MLX model (plug-and-play).
Training
- Base:
sarvamai/sarvam-m(Apache-2.0), quantised to 4-bit with MLX - LoRA: 16 layers, rank 8, lr 1e-5, batch 1, 1 epoch, max length 1,024 (0.08% of weights trained)
- Data: 19600 text chunks (~1,500 chars each), ~70% Hindi. Mix: sangraha_hi: 4051, wiki_en: 6000, fineweb2_hi: 2949, wiki_hi: 7000
- Sources: Hindi + English Wikipedia (CC BY-SA 4.0); Hindi documents mined from AI4Bharat Sangraha (CC BY 4.0) and FineWeb-2 with an Ayurveda keyword-density filter.
- Decontamination: 116 chunks removed that shared any 8-word sequence with a BhashaBench-Ayur question + answer; exam-paper-like pages excluded.
How to use
pip install mlx-lm
mlx_lm.generate --model iamarvind/ayurveda-helper --prompt "आयुर्वेद में त्रिदोष क्या हैं?"
Or search for it in LM Studio (Apple Silicon) and download.
Thinking mode (Sarvam-M's <think> reasoning) is off by default in this release; pass enable_thinking=True to the chat template to turn it on.
Limitations
- Not medical advice. Do not use for diagnosis or treatment.
- Trained on raw text only (no instruction/chat tuning): answers may read like textbook continuations.
- Web-mined text may contain errors and unverified health claims.
Credits
Sarvam AI (base model), AI4Bharat (Sangraha), Hugging Face (FineWeb-2), Wikipedia contributors, BharatGen (BhashaBench-Ayur, AyurParam).
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Model size
24B params
Tensor type
U32
·
BF16 ·
Hardware compatibility
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4-bit
Model tree for iamarvind/ayurveda-helper
Base model
mistralai/Mistral-Small-3.1-24B-Base-2503 Finetuned
sarvamai/sarvam-m