swahili asr audio to text
Overview
This Swahili ASR model provides a specialized pipeline for converting Swahili speech to text, filling a critical gap in low-resource language support for voice-driven applications. For developers, this means the ability to integrate native Swahili transcription into chatbots, accessibility tools, or automated documentation systems without relying on generic multilingual models that often struggle with regional dialects. Built under the Apache-2.0 license, it offers significant flexibility for commercial deployment and local hosting. While it focuses on a specific linguistic domain, it provides the precision necessary for production-grade transcription where high word-error-rate (WER) tolerances are not an option.
Highlights
- Specialized Swahili speech-to-text transcription capabilities
- Apache-2.0 license allows flexible commercial integration
- Optimized for low-resource language accuracy
- Ideal for voice-driven accessibility and automation tools
Usage
Install
# Install Hugging Face transformers
pip install transformers torchSDK Usage
# Load model with transformers
from transformers import AutoModel, AutoTokenizer
model = AutoModel.from_pretrained("Peed911/swahili_asr_audio_to_text")
tokenizer = AutoTokenizer.from_pretrained("Peed911/swahili_asr_audio_to_text")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_hubCLI Download
Download the full repository
Download the full repository
huggingface-cli download Peed911/swahili_asr_audio_to_textDownload 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 Peed911/swahili_asr_audio_to_text config.json --local-dir ./dirSee 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('Peed911/swahili_asr_audio_to_text')Git Download
Make sure git-lfs is installed first
Git Download
git lfs install
git clone https://huggingface.co/Peed911/swahili_asr_audio_to_textTo skip LFS large-file downloads, use:
Skip LFS
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/Peed911/swahili_asr_audio_to_textModel 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 torchLoad the model and run inference
Load the model and run inference
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained('Peed911/swahili_asr_audio_to_text')
tokenizer = AutoTokenizer.from_pretrained('Peed911/swahili_asr_audio_to_text')