Vigyan-Models-GGUF / README.md
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metadata
language:
  - en
tags:
  - gguf
  - vigyan-ai
  - stem
  - physics
  - calculus
  - edge-ai
  - on-device
pipeline_tag: text-generation
license: cc-by-nc-4.0

βš› Vigyan AI: Sovereign Quantized GGUF Suite [Research Preview]

This repository contains official GGUF quantizations of the Vigyan AI STEM Model Series engineered for 100% offline, air-gapped on-device deployment across consumer hardware, laptops, and edge devices.

πŸ“¦ Available Checkpoints & Quantizations

File Quant Method Target Hardware Recommended Context
vigyan-2b-reasoning-q4_k_m.gguf Q4_K_M (1.1 GB) Mobile, WebGPU, 4GB RAM Laptops 4,096 tokens
vigyan-2b-reasoning-q8_0.gguf Q8_0 (1.9 GB) High-precision on-device 8GB Laptops 4,096 tokens

πŸš€ Quickstart via llama.cpp

llama-cli -m vigyan-2b-reasoning-q8_0.gguf -t 4 --temp 0.2 --repeat-penalty 1.15 -p "<|user|>\nExplain Ohm's Law and RC time constant.\n<|assistant|>\n"

πŸ”¬ Research & Experimental Notice

These checkpoints represent intermediate research iterations developed by Vigyan AI to evaluate sovereign neuro-symbolic SLM execution combined with deterministic symbolic solvers (SymPy) and embedded C++ GraphRAG.