Instructions to use esc-bench/wav2vec2-aed-common_voice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use esc-bench/wav2vec2-aed-common_voice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="esc-bench/wav2vec2-aed-common_voice")# Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("esc-bench/wav2vec2-aed-common_voice") model = AutoModelForSpeechSeq2Seq.from_pretrained("esc-bench/wav2vec2-aed-common_voice", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Sanchit Gandhi commited on
Commit ·
66c2e56
1
Parent(s): b4d031f
Correct scripts
Browse files- README.md +6 -4
- run_common_voice.sh +6 -4
README.md
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@@ -12,7 +12,7 @@ To reproduce this run, execute:
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python run_flax_speech_recognition_seq2seq.py \
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--dataset_name="esc-benchmark/esc-datasets" \
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--model_name_or_path="esc-benchmark/wav2vec2-aed-pretrained" \
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--dataset_config_name="
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--output_dir="./" \
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--wandb_name="wav2vec2-aed-common-voice" \
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--wandb_project="wav2vec2-aed" \
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--learning_rate="1e-4" \
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--warmup_steps="500" \
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--logging_steps="25" \
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--max_steps="
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--eval_steps="10000" \
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--save_steps="10000" \
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--generation_max_length="
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--generation_num_beams="
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--generation_length_penalty="1.2" \
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--max_eval_duration_in_seconds="20" \
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--overwrite_output_dir \
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python run_flax_speech_recognition_seq2seq.py \
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--dataset_name="esc-benchmark/esc-datasets" \
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--model_name_or_path="esc-benchmark/wav2vec2-aed-pretrained" \
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--dataset_config_name="common_voice" \
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--output_dir="./" \
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--wandb_name="wav2vec2-aed-common-voice" \
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--wandb_project="wav2vec2-aed" \
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--learning_rate="1e-4" \
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--warmup_steps="500" \
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--logging_steps="25" \
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--max_steps="50001" \
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--eval_steps="10000" \
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--save_steps="10000" \
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--generation_max_length="40" \
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--generation_num_beams="1" \
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--final_generation_max_length="200" \
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--generation_num_beams="14" \
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--generation_length_penalty="1.2" \
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--max_eval_duration_in_seconds="20" \
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--overwrite_output_dir \
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run_common_voice.sh
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python run_flax_speech_recognition_seq2seq.py \
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--dataset_name="esc-benchmark/esc-datasets" \
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--model_name_or_path="esc-benchmark/wav2vec2-aed-pretrained" \
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--dataset_config_name="
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--output_dir="./" \
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--wandb_name="wav2vec2-aed-common-voice" \
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--wandb_project="wav2vec2-aed" \
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@@ -11,11 +11,13 @@ python run_flax_speech_recognition_seq2seq.py \
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--learning_rate="1e-4" \
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--warmup_steps="500" \
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--logging_steps="25" \
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--max_steps="
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--eval_steps="10000" \
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--save_steps="10000" \
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--generation_max_length="
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--generation_num_beams="
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--generation_length_penalty="1.2" \
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--max_eval_duration_in_seconds="20" \
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--overwrite_output_dir \
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python run_flax_speech_recognition_seq2seq.py \
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--dataset_name="esc-benchmark/esc-datasets" \
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--model_name_or_path="esc-benchmark/wav2vec2-aed-pretrained" \
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--dataset_config_name="common_voice" \
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--output_dir="./" \
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--wandb_name="wav2vec2-aed-common-voice" \
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--wandb_project="wav2vec2-aed" \
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--learning_rate="1e-4" \
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--warmup_steps="500" \
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--logging_steps="25" \
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--max_steps="50001" \
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--eval_steps="10000" \
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--save_steps="10000" \
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--generation_max_length="40" \
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--generation_num_beams="1" \
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--final_generation_max_length="200" \
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--generation_num_beams="14" \
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--generation_length_penalty="1.2" \
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--max_eval_duration_in_seconds="20" \
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--overwrite_output_dir \
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