Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
data2vec-audio
Generated from Trainer
Eval Results (legacy)
Instructions to use jjyaoao/Echotune_clean_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jjyaoao/Echotune_clean_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jjyaoao/Echotune_clean_test")# Load model directly from transformers import AutoTokenizer, AutoModelForCTC tokenizer = AutoTokenizer.from_pretrained("jjyaoao/Echotune_clean_test") model = AutoModelForCTC.from_pretrained("jjyaoao/Echotune_clean_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jjyaoao/Echotune_clean_test: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/jjyaoao/Echotune_clean_test/resolve/main/training_args.bin
- Command line
-
hf download hf://jjyaoao/Echotune_clean_test/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jjyaoao/Echotune_clean_test/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- bd8387b8e8d1c0aa733a7901b32c0bb8cb7a55f5f77bbd47177c4df4871161e5
- Size of remote file:
- 3.96 kB
- SHA256:
- c5042584be447640d6d08ef4808082d2d75aa745bfd0921424c932142f0044d2
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