Automatic Speech Recognition
Transformers
PyTorch
JAX
Estonian
wav2vec2
audio
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use manandey/wav2vec2-large-xlsr-estonian with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use manandey/wav2vec2-large-xlsr-estonian with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="manandey/wav2vec2-large-xlsr-estonian")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("manandey/wav2vec2-large-xlsr-estonian") model = AutoModelForCTC.from_pretrained("manandey/wav2vec2-large-xlsr-estonian", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from manandey/wav2vec2-large-xlsr-estonian: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/manandey/wav2vec2-large-xlsr-estonian/resolve/9aae51827ae33c56f1c4d9b35f14f2eb35dc8f2d/pytorch_model.bin
- Command line
-
hf download hf://manandey/wav2vec2-large-xlsr-estonian@9aae51827ae33c56f1c4d9b35f14f2eb35dc8f2d/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/manandey/wav2vec2-large-xlsr-estonian/resolve/9aae51827ae33c56f1c4d9b35f14f2eb35dc8f2d/pytorch_model.bin
1.26 GB
- Xet hash:
- d27d9f70fae82455477f9162ec661175704c16333085b04471aa7f53d0a8b606
- Size of remote file:
- 1.26 GB
- SHA256:
- ab06b55b79e4a9a4b246aef63a247bb59317b0bd169a499a4a6ff1032bdcfa8e
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