Automatic Speech Recognition
Transformers
PyTorch
Chinese
wav2vec2
audio
speech
xlsr-fine-tuning-week
Instructions to use gymeee/demo_code_switching with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gymeee/demo_code_switching with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="gymeee/demo_code_switching")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("gymeee/demo_code_switching") model = AutoModelForCTC.from_pretrained("gymeee/demo_code_switching", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gymeee/demo_code_switching: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/gymeee/demo_code_switching/resolve/main/training_args.bin
- Command line
-
hf download hf://gymeee/demo_code_switching/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gymeee/demo_code_switching/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- a5e9c55c662d2fe8d96b826fd91766faf17e1b97abcfe3c8801e512c83362863
- Size of remote file:
- 3.52 kB
- SHA256:
- b0c5c3dc82aa8e9a47607b8dad54611380f6415bd7500de6281048dc23f7fc53
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