Skip to content

[pull] main from m-bain:main #60

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
pull merged 6 commits into from
Feb 10, 2026
Merged

[pull] main from m-bain:main #60

Changes from all commits
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
2b5ae8c
[BugFix] Type hint fix in decode_batch List[str] not str:
1carlito Feb 9, 2026
570b08b
fix: add no_repeat_ngram_size and repetition_penalty options to Whisp…
Feb 10, 2026
863a986
Merge pull request #1340 from RickSanchez93/main
m-bain Feb 10, 2026
cc6f627
[BugFix] The variable I removed was not being used anyhwere.
1carlito Feb 10, 2026
f2d853a
Merge pull request #1342 from 1carlito/bugs
1carlito Feb 10, 2026
741ab9a
Merge pull request #1343 from m-bain/fix-type-hint-decode-batch
1carlito Feb 10, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
10 changes: 4 additions & 6 deletions whisperx/asr.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -58,11 +58,7 @@ def generate_segment_batched(
)

encoder_output = self.encode(features)

max_initial_timestamp_index = int(
round(options.max_initial_timestamp / self.time_precision)
)


result = self.model.generate(
encoder_output,
[prompt] * batch_size,
Expand All @@ -72,11 +68,13 @@ def generate_segment_batched(
max_length=self.max_length,
suppress_blank=options.suppress_blank,
suppress_tokens=options.suppress_tokens,
no_repeat_ngram_size=options.no_repeat_ngram_size,
repetition_penalty=options.repetition_penalty,
)

tokens_batch = [x.sequences_ids[0] for x in result]

def decode_batch(tokens: List[List[int]]) -> str:
def decode_batch(tokens: List[List[int]]) -> List[str]:
res = []
for tk in tokens:
res.append([token for token in tk if token < tokenizer.eot])
Expand Down