Instructions to use cstr/whisper-large-v3-turbo-german-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cstr/whisper-large-v3-turbo-german-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="cstr/whisper-large-v3-turbo-german-GGUF")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("cstr/whisper-large-v3-turbo-german-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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license:
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pipeline_tag: automatic-speech-recognition
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# whisper-large-v3-turbo-german — GGUF
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license: apache-2.0
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language:
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library_name: transformers
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pipeline_tag: automatic-speech-recognition
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model-index:
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- name: whisper-large-v3-turbo-german by Florian Zimmermeister @primeLine
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results:
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- task:
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type: automatic-speech-recognition
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name: Speech Recognition
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dataset:
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name: German ASR Data-Mix
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type: flozi00/asr-german-mixed
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metrics:
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- type: wer
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value: 2.628 %
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name: Test WER
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datasets:
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- flozi00/asr-german-mixed
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- flozi00/asr-german-mixed-evals
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base_model:
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- primeline/whisper-large-v3-german
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# whisper-large-v3-turbo-german — GGUF
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