Overview

The Sinhala Audio to Text CD model is a specialized speech-to-text tool designed for high-accuracy transcription of the Sinhala language. For developers building localization pipelines or accessibility features, this model bridges a critical gap in South Asian language support. It is particularly effective for converting spoken Sinhala audio into clean text for downstream NLP tasks like sentiment analysis or translation. Licensed under Apache-2.0, it offers the flexibility needed for commercial integration. Compared to general-purpose multilingual models, this focused architecture provides better nuance and phonetic accuracy for Sinhala-specific dialects, making it a reliable choice for region-specific voice interfaces and automated documentation tools.

Highlights

High-precision Sinhala speech-to-text transcription
Apache-2.0 license for flexible commercial deployment
Optimized for regional dialect accuracy
Seamless integration into NLP processing pipelines

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("AqeelShafy7/Sinhala_Audio_to_Text_CD")
tokenizer = AutoTokenizer.from_pretrained("AqeelShafy7/Sinhala_Audio_to_Text_CD")

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

huggingface-cli download AqeelShafy7/Sinhala_Audio_to_Text_CD

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

huggingface-cli download AqeelShafy7/Sinhala_Audio_to_Text_CD config.json --local-dir ./dir

See the official docs for more CLI options

SDK Download

# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('AqeelShafy7/Sinhala_Audio_to_Text_CD')

Git Download

Make sure git-lfs is installed first

Git Download

git lfs install
git clone https://huggingface.co/AqeelShafy7/Sinhala_Audio_to_Text_CD

To skip LFS large-file downloads, use:

Skip LFS

GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/AqeelShafy7/Sinhala_Audio_to_Text_CD

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

pip install -U transformers torch

Load the model and run inference

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained('AqeelShafy7/Sinhala_Audio_to_Text_CD')
tokenizer = AutoTokenizer.from_pretrained('AqeelShafy7/Sinhala_Audio_to_Text_CD')

Full Documentation

来源: HuggingFace

---
license: apache-2.0
base_model: openai/whisper-small
tags:

trnslation

generated_from_trainer

model-index:

name: Sinhala_Audio_to_Text_CD

results: []
---

Sinhala_Audio_to_Text_CD

This model is a fine-tuned version of openai/whisper-small on the None dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-05

train_batch_size: 8

eval_batch_size: 8

seed: 42

gradient_accumulation_steps: 2

total_train_batch_size: 16

optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08

lr_scheduler_type: linear

lr_scheduler_warmup_steps: 500

num_epochs: 10

Training results

Framework versions

Transformers 4.38.2

Pytorch 2.2.1+cpu

Datasets 2.12.0

Tokenizers 0.15.2