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Fine-tuning
control plane
for WhisperX.

Manage audio data, verify transcripts, run training jobs, and benchmark models — all from one interface.

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GPU-Backed
WhisperX inference pipeline
Model word accuracy98%
7Sections
RESTAPI
JWTAuth
ACTIVE
GPU READY

Powered modules

Data Studio
Verification
Training Hub
Model Registry
Benchmarking
Live Metrics
Fine-tuning
Data Studio
Verification
Training Hub
Model Registry
Benchmarking
Live Metrics
Fine-tuning
Data Studio
Verification
Training Hub
Model Registry
Benchmarking
Live Metrics
Fine-tuning

How it works

From raw audio to a fine-tuned model.

01

Upload Audio

Submit audio files. WhisperX transcribes with word-level timestamps.

02

Verify Transcripts

Review AI output word-by-word. Accept, correct, or reject hunks.

03

Train Model

Configure and launch a fine-tuning job on your verified dataset.

04

Activate & Benchmark

Register the new model, compare WER/CER, and activate for inference.

Capabilities

Everything in one place.

Getting Started

Launch your high-performance transcription microservice in minutes with Docker.

1Clone the repository
2Configure your models in GEMINI.md
3Run docker-compose up --build
$git clone https://github.com/your-repo/whisperx.git
$cd whisperx
$docker-compose up --build -d
# API starts on :8002
# Whisper starts on :9000