Automatic Speech Recognition
Transformers
Safetensors
Sediq
whisper
formosanbank
formosan
endangered-languages
speech
asr
whisper-small
tacl
Instructions to use FormosanBank/formosan-asr-taroko with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FormosanBank/formosan-asr-taroko with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="FormosanBank/formosan-asr-taroko")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("FormosanBank/formosan-asr-taroko") model = AutoModelForSpeechSeq2Seq.from_pretrained("FormosanBank/formosan-asr-taroko", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "actual_train_rows": 7650, | |
| "best_selection_cer": 0.026846856509768723, | |
| "best_selection_wer": 0.061902180140190874, | |
| "best_step": 1722, | |
| "condition": "pan_formosan_to_language", | |
| "dominant_hypothesis_rate": 0.005197505197505198, | |
| "estimated_effective_epochs": 3.0002614379084966, | |
| "failures": 0, | |
| "generated_at": "2026-06-25T21:34:57+00:00", | |
| "intended_train_rows": 7650, | |
| "manifest_dir": "/projects/prudlab/tacl_formosan_asr/experiments/manifests/gate5_whisper_final_v1_with_pan_checkpoint/whisper_small_pan_formosan_to_language_train-taroko_eval-taroko-all-corpora_dataset_v1_split_v2_formosan_safe_v1_seed13", | |
| "nonempty_hypothesis_rate": 1.0, | |
| "prediction_rows": 962, | |
| "result_dir": "/scratch/scheppat/projects/tacl_formosan_asr/runs_whisper_final_v1/whisper_small_pan_formosan_to_language_train-taroko_eval-taroko-all-corpora_dataset_v1_split_v2_formosan_safe_v1_seed13", | |
| "result_label": "final", | |
| "run_id": "whisper_small_pan_formosan_to_language_train-taroko_eval-taroko-all-corpora_dataset_v1_split_v2_formosan_safe_v1_seed13", | |
| "status": "pass", | |
| "steps": 2869, | |
| "test_rows": 962, | |
| "train_batch_size": 8, | |
| "warnings": 0 | |
| } | |