whisat-base / infer_hf_whisper.yaml
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# ################################
# Model: Whisper (Encoder-Decoder) + NLL
# Augmentation: TimeDomainSpecAugment
# Authors: Adel Moumen 2022, Titouan Parcollet 2022, Rosy Southwell 2023
# ################################
model_src: rosyvs/whisat-base
model_type: tiny.en
language: english
auto_mix_prec: False # TODO: set to True for CUDA
only_encoder: False
# These values are only used for the searchers.
# They needs to be hardcoded and should not be changed with Whisper.
# They are used as part of the searching process.
# The bos token of the searcher will be timestamp_index
# and will be concatenated with the bos, language and task tokens.
timestamp_index: 50363
eos_index: 50257
bos_index: 50258
# Decoding parameters
min_decode_ratio: 0.0
max_decode_ratio: 1.0 # the commonvoice inference yaml uses 0.1
test_beam_size: 5 # TODO: this was 8, changing to 5 as this is the default used by openAI
whisper: !new:speechbrain.lobes.models.huggingface_whisper.HuggingFaceWhisper
encoder_only: !ref <only_encoder>
freeze: True
freeze_encoder: True
source: !ref <model_src>
save_path: !ref <cache_dir>
# language: language
# tokenizer: !new:speechbrain.lobes.models.huggingface_whisper.HuggingFaceWhisper
# encoder_only: False
# freeze: True
# freeze_encoder: True
# source: !ref openai/whisper-<model_type>
# save_path: !ref <cache_dir>
# decoder: !new:speechbrain.decoders.seq2seq.S2SWhisperGreedySearch
# model: !ref <whisper>
# bos_index: !ref <timestamp_index>
# eos_index: !ref <eos_index>
# min_decode_ratio: !ref <min_decode_ratio>
# max_decode_ratio: !ref <max_decode_ratio>
decoder: !new:speechbrain.decoders.seq2seq.S2SWhisperBeamSearch
module: [!ref <whisper>]
bos_index: !ref <timestamp_index>
eos_index: !ref <eos_index>
min_decode_ratio: !ref <min_decode_ratio>
max_decode_ratio: !ref <max_decode_ratio>
beam_size: !ref <test_beam_size>
modules:
whisper: !ref <whisper>
# tokenizer: !ref <tokenizer>
decoder: !ref <decoder> # can change to greedy
pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
loadables:
whisper: !ref <whisper>
# tokenizer: !ref <tokenizer>
# decoder: !ref <decoder>
# paths:
# whisper: !ref <model_src>/whisper.ckpt
# tokenizer: !ref openai/whisper-<model_type>
# decoder: !ref <model_src>/whisper.ckpt
# checkpointer: !new:speechbrain.utils.checkpoints.Checkpointer
# checkpoints_dir: !ref <model_src>
# recoverables:
# whisper: !ref <whisper>