---
license: apache-2.0
base_model: distil-whisper/distil-large-v3.5
tags:
- whisper
- automatic-speech-recognition
- audio
- hf-asr-leaderboard
- hindi
- medical
- indic
- multilingual
language:
- hi
- en
- bn
- ta
- te
- gu
- kn
- ml
- mr
- pa
- ur
library_name: transformers
pipeline_tag: automatic-speech-recognition
---

# United Medical ASR Indic (Accelerated Training)

This model is a fine-tuned version of [distil-whisper/distil-large-v3.5](https://huggingface.co/distil-whisper/distil-large-v3.5) for multilingual medical speech recognition across Indian languages, trained using HuggingFace Accelerate for optimal performance.

## Performance Optimizations

- **Multi-GPU Training**: Distributed training across available GPUs
- **Mixed Precision**: FP16 training for 2x speed improvement
- **Gradient Accumulation**: Effective large batch sizes
- **Memory Optimization**: Gradient checkpointing and efficient data loading
- **Batch Processing**: Locations processed in optimized batches

## Model Description

- **Base Model**: distil-whisper/distil-large-v3.5
- **Languages**: Multiple Indian languages (Hindi, English, Bengali, Tamil, Telugu, Gujarati, Kannada, Malayalam, Marathi, Punjabi, Urdu)
- **Domain**: Medical ASR for Indic languages
- **Training**: Accelerated sequential fine-tuning with batch processing

## Usage

```python
from transformers import WhisperProcessor, WhisperForConditionalGeneration
import torch

processor = WhisperProcessor.from_pretrained("abar-uwc/united-med-asr-indic")
model = WhisperForConditionalGeneration.from_pretrained("abar-uwc/united-med-asr-indic")

# The model will automatically detect and transcribe in the appropriate language
```