modal-examples
whisper_mic
| modal-examples | whisper_mic | |
|---|---|---|
| 9 | 2 | |
| 572 | 632 | |
| 5.6% | - | |
| 9.5 | 7.2 | |
| 5 days ago | 28 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.
modal-examples
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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
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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.
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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...
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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.
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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...
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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...
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How can machine learning help us learn languages better?
Transcription - OpenAI just released Whisper. Check out what it can do with podcasts
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[P] Transcribe any podcast episode in just 1 minute with optimized OpenAI/whisper
Here's the source code.
whisper_mic
- I've built a few tools on top of GPT-3.5 (text generation, q&a with embeddings). AMA about resources and AI dev stacks for building with OpenAI's APIs
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Whispers AI Modular Future
What utilities related to Whisper do you wish existed? What have you had to build yourself?
On the end user application side, I wish there was something that let me pick a podcast of my choosing, get it fully transcribed, and get an embeddings search plus answer q&a on top of that podcast or set of chosen podcasts. I've seen ones for specific podcasts, but I'd like one where I can choose the podcast. (Probably won't build it)
Also on the end user side, I wish there was an Otter alternative (still paid $30/mo, but unlimited minutes per month) that had longer transcription limits. (Started building this, not much interest from users though)
Things I've seen on the dev tool side:
Gladia (API call version of Whisper)
Whisper.cpp
Whisper webservice (https://github.com/ahmetoner/whisper-asr-webservice) - via this thread
Live microphone demo (not real time, it still does it in chunks) https://github.com/mallorbc/whisper_mic
Streamlit UI https://github.com/hayabhay/whisper-ui
Whisper playground https://github.com/saharmor/whisper-playground
Real time whisper https://github.com/shirayu/whispering
Whisper as a service https://github.com/schibsted/WAAS
Improved timestamps and speaker identification https://github.com/m-bain/whisperX
MacWhisper https://goodsnooze.gumroad.com/l/macwhisper
Crossplatform desktop Whisper that supports semi-realtime https://github.com/chidiwilliams/buzz
What are some alternatives?
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
WAAS - Whisper as a Service (GUI and API with queuing for OpenAI Whisper)
FlexGen - Running large language models on a single GPU for throughput-oriented scenarios.
frogbase - Transform audio-visual content into navigable knowledge.
whisperX - WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization)
EasyLM - Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Flax.
whisper - Robust Speech Recognition via Large-Scale Weak Supervision
mlc-llm - Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.
whisper-playground - Build real time speech2text web apps using OpenAI's Whisper https://openai.com/blog/whisper/
brev-cli - Connect your laptop to cloud computers. Follow to stay updated about our product