Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
hubert
Generated from Trainer
Eval Results (legacy)
Instructions to use kksukk/hubert_zeroth_gpu_scratch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kksukk/hubert_zeroth_gpu_scratch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="kksukk/hubert_zeroth_gpu_scratch")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("kksukk/hubert_zeroth_gpu_scratch") model = AutoModelForCTC.from_pretrained("kksukk/hubert_zeroth_gpu_scratch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kksukk/hubert_zeroth_gpu_scratch: direct link, hf CLI and curl.
- Browser
- Download file 381 MB
-
https://huggingface.co/kksukk/hubert_zeroth_gpu_scratch/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kksukk/hubert_zeroth_gpu_scratch/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kksukk/hubert_zeroth_gpu_scratch/resolve/main/pytorch_model.bin
381 MB
- Xet hash:
- 83e88f64888bc0a57162877e896b2af5043361574eeeab8c65bbb0bcb33fc017
- Size of remote file:
- 381 MB
- SHA256:
- 6389f7d56c7f71b1a5887c73b6d1dc4227915a706357f4ccc5aaf648c67a728a
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