Automatic Speech Recognition
Transformers
Safetensors
Persian
wav2vec2
audio
speech
asr
Eval Results (legacy)
Instructions to use lnxdx/Wav2Vec2-Large-XLSR-Persian-ShEMO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lnxdx/Wav2Vec2-Large-XLSR-Persian-ShEMO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lnxdx/Wav2Vec2-Large-XLSR-Persian-ShEMO")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("lnxdx/Wav2Vec2-Large-XLSR-Persian-ShEMO") model = AutoModelForCTC.from_pretrained("lnxdx/Wav2Vec2-Large-XLSR-Persian-ShEMO", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from lnxdx/Wav2Vec2-Large-XLSR-Persian-ShEMO: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/lnxdx/Wav2Vec2-Large-XLSR-Persian-ShEMO/resolve/main/training_args.bin
- Command line
-
hf download hf://lnxdx/Wav2Vec2-Large-XLSR-Persian-ShEMO/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/lnxdx/Wav2Vec2-Large-XLSR-Persian-ShEMO/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- 4316faa6f6f25e194cce58e614d70b7ab017a5b5850e003dc9a2add3eede735b
- Size of remote file:
- 4.66 kB
- SHA256:
- 6667d929fee99d07345e57d4876c1009c30b2915c37843db22a8d0f29919d030
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