Instructions to use nullonesix/training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nullonesix/training with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nullonesix/training")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("nullonesix/training") model = AutoModelForSpeechSeq2Seq.from_pretrained("nullonesix/training") - Notebooks
- Google Colab
- Kaggle
| python run_eval.py \ | |
| --model_name_or_path "openai/whisper-tiny.en" \ | |
| --dataset_name "librispeech_asr+librispeech_asr+common_voice_13_0+voxpopuli+ami-ihm+ami-sdm+peoples_speech-clean+tedlium+switchboard-data+gigaspeech-l+spgispeech+chime4+google/fleurs+sanchit-gandhi/earnings22_split_resampled" \ | |
| --dataset_config_name "all+all+en+en+ihm+sdm+clean+release3+all+l+L+1-channel+en_us+default" \ | |
| --dataset_split_name "validation.clean+validation.other+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation" \ | |
| --text_column_name "text+text+text+text+text+text+text+text+text+text+text+text+transcription+sentence" \ | |
| --cache_dir "/home/sanchitgandhi/.cache" \ | |
| --dataset_cache_dir "/home/sanchitgandhi/.cache" \ | |
| --output_dir "./" \ | |
| --wandb_dir "/home/sanchitgandhi/.cache" \ | |
| --wandb_project "distil-whisper-eval" \ | |
| --wandb_name "tiny.en" \ | |
| --per_device_eval_batch_size 32 \ | |
| --dtype "bfloat16" \ | |
| --dataloader_num_workers 0 \ | |
| --report_to "wandb" \ | |
| --streaming \ | |
| --predict_with_generate | |
| python run_eval.py \ | |
| --model_name_or_path "openai/whisper-base.en" \ | |
| --dataset_name "librispeech_asr+librispeech_asr+common_voice_13_0+voxpopuli+ami-ihm+ami-sdm+peoples_speech-clean+tedlium+switchboard-data+gigaspeech-l+spgispeech+chime4+google/fleurs+sanchit-gandhi/earnings22_split_resampled" \ | |
| --dataset_config_name "all+all+en+en+ihm+sdm+clean+release3+all+l+L+1-channel+en_us+default" \ | |
| --dataset_split_name "validation.clean+validation.other+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation" \ | |
| --text_column_name "text+text+text+text+text+text+text+text+text+text+text+text+transcription+sentence" \ | |
| --cache_dir "/home/sanchitgandhi/.cache" \ | |
| --dataset_cache_dir "/home/sanchitgandhi/.cache" \ | |
| --output_dir "./" \ | |
| --wandb_dir "/home/sanchitgandhi/.cache" \ | |
| --wandb_project "distil-whisper-eval" \ | |
| --wandb_name "base.en" \ | |
| --per_device_eval_batch_size 32 \ | |
| --dtype "bfloat16" \ | |
| --dataloader_num_workers 0 \ | |
| --report_to "wandb" \ | |
| --streaming \ | |
| --predict_with_generate | |
| python run_eval.py \ | |
| --model_name_or_path "openai/whisper-small.en" \ | |
| --dataset_name "librispeech_asr+librispeech_asr+common_voice_13_0+voxpopuli+ami-ihm+ami-sdm+peoples_speech-clean+tedlium+switchboard-data+gigaspeech-l+spgispeech+chime4+google/fleurs+sanchit-gandhi/earnings22_split_resampled" \ | |
| --dataset_config_name "all+all+en+en+ihm+sdm+clean+release3+all+l+L+1-channel+en_us+default" \ | |
| --dataset_split_name "validation.clean+validation.other+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation" \ | |
| --text_column_name "text+text+text+text+text+text+text+text+text+text+text+text+transcription+sentence" \ | |
| --cache_dir "/home/sanchitgandhi/.cache" \ | |
| --dataset_cache_dir "/home/sanchitgandhi/.cache" \ | |
| --output_dir "./" \ | |
| --wandb_dir "/home/sanchitgandhi/.cache" \ | |
| --wandb_project "distil-whisper-eval" \ | |
| --wandb_name "small.en" \ | |
| --per_device_eval_batch_size 32 \ | |
| --dtype "bfloat16" \ | |
| --dataloader_num_workers 0 \ | |
| --report_to "wandb" \ | |
| --streaming \ | |
| --predict_with_generate | |
| python run_eval.py \ | |
| --model_name_or_path "openai/whisper-medium.en" \ | |
| --dataset_name "librispeech_asr+librispeech_asr+common_voice_13_0+voxpopuli+ami-ihm+ami-sdm+peoples_speech-clean+tedlium+switchboard-data+gigaspeech-l+spgispeech+chime4+google/fleurs+sanchit-gandhi/earnings22_split_resampled" \ | |
| --dataset_config_name "all+all+en+en+ihm+sdm+clean+release3+all+l+L+1-channel+en_us+default" \ | |
| --dataset_split_name "validation.clean+validation.other+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation" \ | |
| --text_column_name "text+text+text+text+text+text+text+text+text+text+text+text+transcription+sentence" \ | |
| --cache_dir "/home/sanchitgandhi/.cache" \ | |
| --dataset_cache_dir "/home/sanchitgandhi/.cache" \ | |
| --output_dir "./" \ | |
| --wandb_dir "/home/sanchitgandhi/.cache" \ | |
| --wandb_project "distil-whisper-eval" \ | |
| --wandb_name "medium.en" \ | |
| --per_device_eval_batch_size 32 \ | |
| --dtype "bfloat16" \ | |
| --dataloader_num_workers 0 \ | |
| --report_to "wandb" \ | |
| --streaming \ | |
| --predict_with_generate | |
| python run_eval.py \ | |
| --model_name_or_path "openai/whisper-large-v2" \ | |
| --dataset_name "librispeech_asr+librispeech_asr+common_voice_13_0+voxpopuli+ami-ihm+ami-sdm+peoples_speech-clean+tedlium+switchboard-data+gigaspeech-l+spgispeech+chime4+google/fleurs+sanchit-gandhi/earnings22_split_resampled" \ | |
| --dataset_config_name "all+all+en+en+ihm+sdm+clean+release3+all+l+L+1-channel+en_us+default" \ | |
| --dataset_split_name "validation.clean+validation.other+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation" \ | |
| --text_column_name "text+text+text+text+text+text+text+text+text+text+text+text+transcription+sentence" \ | |
| --cache_dir "/home/sanchitgandhi/.cache" \ | |
| --dataset_cache_dir "/home/sanchitgandhi/.cache" \ | |
| --output_dir "./" \ | |
| --wandb_dir "/home/sanchitgandhi/.cache" \ | |
| --wandb_project "distil-whisper-eval" \ | |
| --wandb_name "large-v2" \ | |
| --per_device_eval_batch_size 16 \ | |
| --dtype "bfloat16" \ | |
| --dataloader_num_workers 0 \ | |
| --report_to "wandb" \ | |
| --streaming \ | |
| --predict_with_generate |