Instructions to use seyyedaliayati/zoom_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seyyedaliayati/zoom_model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("seyyedaliayati/zoom_model", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use seyyedaliayati/zoom_model with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for seyyedaliayati/zoom_model to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for seyyedaliayati/zoom_model to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for seyyedaliayati/zoom_model to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="seyyedaliayati/zoom_model", max_seq_length=2048, )
metadata
base_model: unsloth/llama-3.2-3b-instruct-bnb-4bit
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
license: cc
language:
- en
Making Acoustic Side-Channel Attacks on Noisy Keyboards Viable with LLM-Assisted Spectrograms "Typo" Correction
Model Overview
This is a fine-tuned version of the LLaMA-3.2-3B model for Acoustic Side-Channel Attacks (ASCA), designed to improve keystroke classification and error correction in noisy environments. The model leverages Vision Transformers (VTs) for spectrogram classification and Large Language Models (LLMs) for typo correction.
- Fine-Tuned From: unsloth/llama-3.2-3b-instruct-bnb-4bit
- License: CC
- Developed by: Seyyed Ali Ayati, Jin Hyun Park, Yichen Cai, Marcus Botacin
- Repository: EchoCrypt GitHub
Citation
If you use this model, please cite the following paper:
@article{ayati2025making,
title={Making Acoustic Side-Channel Attacks on Noisy Keyboards Viable with LLM-Assisted Spectrograms' "Typo" Correction},
author={Ayati, Seyyed Ali and Park, Jin Hyun and Cai, Yichen and Botacin, Marcus},
journal={arXiv preprint arXiv:2504.11622},
year={2025},
url={https://arxiv.org/abs/2504.11622}
}