mt5 small denoising en es final

ProviderEshan210352R
Categoryspeech-enhancement
LicenseApache-2.0
Downloads10
Stars0

Overview

The mt5-small-denoising model is a specialized speech-enhancement tool designed to remove background noise from audio signals in English and Spanish. Built on the mT5 architecture, this model leverages multilingual pre-training to handle acoustic variances across different languages, making it an efficient choice for developers building voice-to-text pipelines or communication apps. Unlike general-purpose noise gates, this model focuses on signal reconstruction to preserve vocal clarity. It is lightweight enough for edge deployment or as a preprocessing layer in larger ASR (Automatic Speech Recognition) workflows, offering a balance between computational overhead and audio fidelity.

Highlights

  • Dual-language support for English and Spanish audio denoising
  • Lightweight architecture suitable for low-latency edge deployment
  • Ideal preprocessing step for improving ASR transcription accuracy
  • Open-source Apache-2.0 license for flexible commercial integration

Usage

Install
# Install Hugging Face transformers
pip install transformers torch
SDK Usage
# Load model with transformers
from transformers import AutoModel, AutoTokenizer

model = AutoModel.from_pretrained("Eshan210352R/mt5-small-denoising-en-es-final")
tokenizer = AutoTokenizer.from_pretrained("Eshan210352R/mt5-small-denoising-en-es-final")

Hugging Face Download

We recommend downloading the model via the Hugging Face CLI or Hub SDK.

Guidance：Before downloading, install huggingface_hub with:

Guidance 
pip install -U huggingface_hub

CLI Download

Download the full repository

Download the full repository 
huggingface-cli download Eshan210352R/mt5-small-denoising-en-es-final

Download a single file to a local folder (e.g. config.json into ./dir)

Download a single file to a local folder (e.g. config.json into ./dir) 
huggingface-cli download Eshan210352R/mt5-small-denoising-en-es-final config.json --local-dir ./dir

See the official docs for more CLI options

SDK Download

SDK Download 
# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('Eshan210352R/mt5-small-denoising-en-es-final')

Git Download

Make sure git-lfs is installed first

Git Download 
git lfs install
git clone https://huggingface.co/Eshan210352R/mt5-small-denoising-en-es-final

To skip LFS large-file downloads, use:

Skip LFS 
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/Eshan210352R/mt5-small-denoising-en-es-final

Model files are hosted on the Hugging Face Hub — download directly via HF CLI / SDK / Git, not through this site.

PyTorch / Transformers Usage

Install Transformers

Install Transformers 
pip install -U transformers torch

Load the model and run inference

Load the model and run inference 
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained('Eshan210352R/mt5-small-denoising-en-es-final')
tokenizer = AutoTokenizer.from_pretrained('Eshan210352R/mt5-small-denoising-en-es-final')

Full Documentation

来源: HuggingFace

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library_name: transformers
tags: []
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