Whisper Large V3 Turbo German Ct2

🚀 Whisper Large V3 Turbo German Model

This model is a CTranslate2 translation of a fine - tuned Whisper Large v3 for German speech recognition, offering high - performance in various German - related speech applications.

🚀 Quick Start

This model is just a CTranslate2 Translation, for usage in CTranslate conform frameworks such as faster - whisper. For any questions about the fine - tuning method or the dataset used please refer to the original Repo [primeline/whisper - large - v3 - turbo - german](https://huggingface.co/primeline/whisper - large - v3 - turbo - german)

✨ Features

Summary

This model map provides information about a model based on Whisper Large v3 that has been fine - tuned for speech recognition in German. Whisper is a powerful speech recognition platform developed by OpenAI. This model has been specially optimized for processing and recognizing German speech.

Applications

This model can be used in various application areas, including:

• Transcription of spoken German language
• Voice commands and voice control
• Automatic subtitling for German videos
• Voice - based search queries in German
• Dictation functions in word processing programs

📦 Model family

🔧 Technical Details

Evaluations - Word error rate

The data and code for evaluations are available [here](https://huggingface.co/datasets/flozi00/asr - german - mixed - evals)

Training data

The training data for this model includes a large amount of spoken German from various sources. The data was carefully selected and processed to optimize recognition performance.

Training process

The training of the model was performed with the following hyperparameters:

• Batch size: 12288
• Epochs: 3
• Learning rate: 1e - 6
• Data augmentation: No
• Optimizer: Ademamix

💻 Usage Examples

Basic Usage

import torch
from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor, pipeline
from datasets import load_dataset
device = "cuda:0" if torch.cuda.is_available() else "cpu"
torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
model_id = "primeline/whisper-large-v3-turbo-german"
model = AutoModelForSpeechSeq2Seq.from_pretrained(
    model_id, torch_dtype=torch_dtype, low_cpu_mem_usage=True, use_safetensors=True
)
model.to(device)
processor = AutoProcessor.from_pretrained(model_id)
pipe = pipeline(
    "automatic-speech-recognition",
    model=model,
    tokenizer=processor.tokenizer,
    feature_extractor=processor.feature_extractor,
    max_new_tokens=128,
    chunk_length_s=30,
    batch_size=16,
    return_timestamps=True,
    torch_dtype=torch_dtype,
    device=device,
)
dataset = load_dataset("distil-whisper/librispeech_long", "clean", split="validation")
sample = dataset[0]["audio"]
result = pipe(sample)
print(result["text"])

📄 License

This model is licensed under the Apache 2.0 license.

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Model author: Florian Zimmermeister