Model reference · open weights
whisper-large-german is an open-weight audio or speech model from primeline. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | primeline |
|---|---|
| Type | Audio & music |
| Task | Speech→text |
| Parameters (lead) | 809M |
| Runs with | transformers |
| Based on | primeline/whisper-large-v3-german |
| Released | 2024-10-02 |
| Popularity | 425k downloads / month |
| Licence | Open weights |
About
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.
This model can be used in various application areas, including
| Model | Parameters | link |
|---|---|---|
| Whisper large v3 german | 1.54B | link |
| Whisper large v3 turbo german | 809M | link |
| Distil-whisper large v3 german | 756M | link |
| tiny whisper | 37.8M | link |
| Dataset | openai-whisper-large-v3-turbo | openai-whisper-large-v3 | primeline-whisper-large-v3-german | nyrahealth-CrisperWhisper (large) | primeline-whisper-large-v3-turbo-german |
|---|---|---|---|---|---|
| Tuda-De | 8.300 | 7.884 | 7.711 | 5.148 | 6.441 |
| common_voice_19_0 | 3.849 | 3.484 | 3.215 | 1.927 | 3.200 |
| multilingual librispeech | 3.203 | 2.832 | 2.129 | 2.815 | 2.070 |
| All | 3.649 | 3.279 | 2.734 | 2.662 | 2.628 |
The data and code for evaluations are available here
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.
The training of the model was performed with the following hyperparameters
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"])
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Model author: Florian Zimmermeister
Disclaimer
This model is not a product of the primeLine Group.
It represents research conducted by [Florian Zimmermeister](https://huggingface.co/flozi00), with computing power sponsored by primeLine.
The model is published under this account by primeLine, but it is not a commercial product of primeLine Solutions GmbH.
Please be aware that while we have tested and developed this model to the best of our abilities, errors may still occur.
Use of this model is at your own risk. We do not accept liability for any incorrect outputs generated by this model.
From the published model card. Full card on the HuggingFace links in the sidebar.
Benchmarks
As published on the model card — the maker's own numbers, not measured by AxForge.
| Task | Dataset | Metric | Score |
|---|---|---|---|
| Speech Recognition | German ASR Data-Mix | Test WER |
Using it via the API
Once AxForge deploys whisper-large-german for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (whisper-large-german below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/audio/transcriptions \ -H "Authorization: Bearer $AXFORGE_API_KEY" \ -F model="whisper-large-german" -F file=@audio.mp3
Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.