SCODE
AI Labs
SCODE
AI Labs
A universal voice assistant and multimodal AI platform uniting GitHub codebase structure with Hugging Face open weights. Developed by Atubra Abraham (SCode).
SCodeGit/SCodeAI
kimbon/scodeai-v1
Safetensors (13.5 GB)
SCodeAI bridges offline application utility with state-of-the-art model distribution. While the core codebase, voice scripts, and system handlers are housed in the SCodeGit/SCodeAI GitHub repository, the optimized model weights (`models/scode_ai_safetensors` and v1 checkpoints) are distributed directly via Hugging Face (`kimbon/scodeai-v1`).
Contains Python scripts (`voice_assistant.py`, `chat.py`), Vosk offline speech files (`vosk-model-small-en-us`), and training directories.
Hosts kimbon/scodeai-v1, providing seamless access to high-performance safetensors weights for transformer pipelines.
Integrates local intent parsers and speech-to-text engines to ensure full system control under personal user management.
Clone the repository from GitHub and pull model weights from Hugging Face:
# 1. Clone GitHub Architecture
git clone https://github.com/SCodeGit/SCodeAI.git
cd SCodeAI
# 2. Setup virtual environment & dependencies
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
# 3. Load Hugging Face weights in Python pipeline
from transformers import AutoTokenizer, AutoModelForCausalLM
model_id = "kimbon/scodeai-v1"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")Operating with a privacy-first standard, SCodeAI combines local repository scripts with open-weights distribution so your operational environment remains secure and entirely under your control.
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