Instructions to use GENG/hubert_ls_2500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GENG/hubert_ls_2500 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="GENG/hubert_ls_2500")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("GENG/hubert_ls_2500") model = AutoModelForCTC.from_pretrained("GENG/hubert_ls_2500", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload vocab_ls.json
58a0fbe -
Upload training_args.bin
31ea21e -
Upload trainer_state.json
512d2e3 -
Upload scheduler.pt
29c1c72 -
Upload scaler.pt
8813b69 -
Upload rng_state.pth
299c9de -
Upload pytorch_model.bin
0476e34 -
Upload preprocessor_config.json
a3c2ab8 -
Upload optimizer.pt
aad4929 -
Upload config.json
cad0146 -
initial commit
8bfbb7f