ManiKumarAdapala/indic-transcribe-core-8bit

Indic-Transcribe-Core 8-bit

An 8-bit quantized version of Bodhan AI's Indic-Transcribe-Core, created using BitsAndBytes quantization.

The model retains the capabilities of the original multilingual ASR model while significantly reducing GPU memory requirements, making it more suitable for resource-constrained inference and serving multiple users.

Key Features

• —🎙️ Multilingual Automatic Speech Recognition
• —🇮🇳 Supports Indian languages
• —⚡ 8-bit quantization using BitsAndBytes
• —💾 Reduced GPU VRAM usage
• —🔌 Designed for efficient inference and deployment

VRAM Usage

Actual memory usage may vary depending on GPU, batch size, audio duration, and inference configuration.

Base Model

This model is derived from:

[bodhan-ai/indic-transcribe-core](https://huggingface.co/bodhan-ai/indic-transcribe-core)

Please refer to the original model card for the architecture, training details, supported languages, benchmarks, limitations, and licensing information.

Quantization

The model was quantized to 8-bit using BitsAndBytes.

The primary goal of this quantized release is to reduce GPU memory consumption while maintaining the capabilities of the original model.

Inference

For a complete inference example, see the Inference Notebook.

Intended Use

Suitable for:

• —Indian-language speech-to-text
• —Voice applications
• —Multilingual transcription
• —Low-VRAM GPU deployment
• —Multi-user ASR serving
• —On-premise and edge-oriented inference

Attribution

This is a quantized derivative of Bodhan AI's Indic-Transcribe-Core. Please retain the original model's attribution and comply with its license and usage requirements.

Disclaimer

This repository contains an 8-bit quantized version of the original model. Performance, accuracy, memory usage, and compatibility may vary depending on the inference environment.