yt-whisper
modal-examples
| yt-whisper | modal-examples | |
|---|---|---|
| 3 | 9 | |
| 1,316 | 560 | |
| - | 3.6% | |
| 0.0 | 9.5 | |
| 4 months ago | 6 days ago | |
| Python | Python | |
| MIT License | MIT License |
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.
yt-whisper
-
me in real life
#28 transcribe local files
-
YouTubeTranscript.com
Or even better, yt-whisper, which uses OpenAI's Whisper speech to text. I guess it'd be better to first check whether the video has captions first before Whispering, so maybe both your command and this one could be used together.
https://github.com/m1guelpf/yt-whisper
-
[P] Transcribe any podcast episode in just 1 minute with optimized OpenAI/whisper
With minimal changes to https://github.com/m1guelpf/yt-whisper i got a setup to transcribe subs from YouTube videos or local files bit it might take an hour or so running the large model on my CPU.
modal-examples
-
Show HN: Real-time image autocomplete in <100 lines of code with SDXL Lightning
We made a small app for SDXL Lightning, running your own Python code on GPUs. It generates images in real time.
https://potatoes.ai/
We know there was a fal.ai post yesterday, and that got a lot of interest, but we also made this demo yesterday and didn't share — just wanted to mention it as an alternative option for people who like running their own code and custom models instead of using a prebuilt API provider.
The backend code is open-source too and you can deploy it yourself: https://github.com/modal-labs/modal-examples/blob/main/06_gpu_and_ml/stable_diffusion/stable_diffusion_xl_lightning.py
-
Our startup has docs issues and it is costing us prospects. What things can you share to help us?
The startup I work at is relatively pretty good at documentation engineering. We have written code to test the code snippets in docstrings (https://github.com/modal-labs/pytest-markdown-docs) and we have written code to do synthetic monitoring testing of the examples in our examples repo (https://github.com/modal-labs/modal-examples). We are also diligent about putting using Python's warnings library to handle API deprecation, and treat deprecation warnings as errors internally, ensuring our own code samples and examples are most up-to-date.
-
OpenLLaMA: An Open Reproduction of LLaMA
You can get it running with one Python script on Modal.com :)
https://github.com/modal-labs/modal-examples/blob/main/06_gp...
-
Whispers AI Modular Future
This demo lets you choose the podcast, and is open-source: https://modal-labs--whisper-pod-transcriber-fastapi-app.moda...
https://github.com/modal-labs/modal-examples/tree/main/06_gp...
Transcribes 1hr of audio in roughly 1min, using parallelisation across CPUs.
-
Show HN: PodText.ai – Search anything said on a podcast, Highlight text to play
This demo is open-source: https://github.com/modal-labs/modal-examples/tree/main/06_gp....
https://modal-labs--whisper-pod-transcriber-fastapi-app.moda...
-
Show HN: Stable Diffusion Pokémon Cards
It's become so easy to stick together ML models, often without training most or all of them yourself.
*video demo:* https://youtu.be/mQsMuM8d4Qc
*cloud platform:* https://modal.com
*code*: https://github.com/modal-labs/modal-examples/tree/main/06_gp...
-
How can machine learning help us learn languages better?
Transcription - OpenAI just released Whisper. Check out what it can do with podcasts
-
[P] Transcribe any podcast episode in just 1 minute with optimized OpenAI/whisper
Here's the source code.
What are some alternatives?
subsai - 🎞️ Subtitles generation tool (Web-UI + CLI + Python package) powered by OpenAI's Whisper and its variants 🎞️
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
ChatGPT-YouTube-summarizer - This Chrome extension lets you summarize YouTube videos using the ChatGPT.
FlexGen - Running large language models on a single GPU for throughput-oriented scenarios.
tldwol - Web API that summarizes multimedia from various sources using modern AI tools.
WAAS - Whisper as a Service (GUI and API with queuing for OpenAI Whisper)
auto-subtitle - Automatically generate and overlay subtitles for any video.
EasyLM - Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Flax.
gentle - gentle forced aligner
mlc-llm - Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.
malayalam_english_subtitle_generator - Malayalam to English Subtitle Generator for audio files using OpenAI's Whisper.
brev-cli - Connect your laptop to cloud computers. Follow to stay updated about our product