Automatic Speech Recognition
Transformers
PyTorch
JAX
German
wav2vec2
audio
hf-asr-leaderboard
mozilla-foundation/common_voice_6_0
robust-speech-event
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use jonatasgrosman/wav2vec2-large-xlsr-53-german with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonatasgrosman/wav2vec2-large-xlsr-53-german with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/wav2vec2-large-xlsr-53-german")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/wav2vec2-large-xlsr-53-german") model = AutoModelForCTC.from_pretrained("jonatasgrosman/wav2vec2-large-xlsr-53-german", device_map="auto") - Notebooks
- Google Colab
- Kaggle
GGUF + pure-C++ runtime in CrispASR (German XLSR-53)
#4 opened 3 months ago
by
cstr
Librarian Bot: Add base_model information to model
#3 opened over 2 years ago
by
librarian-bot
Adding `safetensors` variant of this model
1
#2 opened over 3 years ago
by
SFconvertbot
Tokenizer missing?
1
#1 opened almost 4 years ago
by
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