whisper-timestamped VS zeta

Compare whisper-timestamped vs zeta and see what are their differences.

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whisper-timestamped zeta
2 1
1,547 254
7.4% -
8.1 9.8
17 days ago 6 days ago
Python Python
GNU Affero General Public License v3.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

whisper-timestamped

Posts with mentions or reviews of whisper-timestamped. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-11-01.

zeta

Posts with mentions or reviews of zeta. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing whisper-timestamped and zeta you can also consider the following projects:

pywhisper - openai/whisper + extra features

petals - 🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading

wav2vec - pure numpy implementation of wav2vec 2.0

LOGICGUIDE - Plug in and Play implementation of "Certified Reasoning with Language Models" that elevates model reasoning by 40%

pyannote-whisper

speechbrain - A PyTorch-based Speech Toolkit

SincNet - SincNet is a neural architecture for efficiently processing raw audio samples.

DALLE-pytorch - Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch

FFmpeg - Mirror of https://git.ffmpeg.org/ffmpeg.git

Chinese-CLIP - Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.

filler-word-removal

transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.