Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use Roxysun/cs2no-wav2vec2-large-xls-r-300m-cs-colab-phoneme with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Roxysun/cs2no-wav2vec2-large-xls-r-300m-cs-colab-phoneme with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Roxysun/cs2no-wav2vec2-large-xls-r-300m-cs-colab-phoneme")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Roxysun/cs2no-wav2vec2-large-xls-r-300m-cs-colab-phoneme") model = AutoModelForCTC.from_pretrained("Roxysun/cs2no-wav2vec2-large-xls-r-300m-cs-colab-phoneme", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c43d4ba7715aa86941abb088b3922d77582455a7c31f8bf407ab3c7f858dd798
- Size of remote file:
- 1.26 GB
- SHA256:
- e3a7404ea5d90ca4783f4715d86d9748e4dc8da4e7f2f865673b274d865d35aa
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