frogbase
FlexGen
frogbase | FlexGen | |
---|---|---|
14 | 39 | |
754 | 9,022 | |
- | 0.9% | |
4.3 | 3.5 | |
7 months ago | 25 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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frogbase
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For people who tried whisper
If you’re looking to use a local deployment and are comfortable with python projects, this deployment was fairly easy to use: https://github.com/hayabhay/whisper-ui
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I have a two-step process for taking notes on transcripts that I'd like to share, but am also looking for feedback for the final step
I recommend using chat GPT to learn some very basic python/programming tho. I like this one https://github.com/hayabhay/whisper-ui which uses streamlit for easy to use UI for bulk transcriptions.
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(Preferably) Self Hosted Podcasts with searchable transcripts
This tool 2 out of the 4 items you mentioned: https://github.com/hayabhay/whisper-ui
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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
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[P] Whisper-UI Update: You can now bulk-transcribe, save & search transcriptions with Streamlit & SQLAlchemy 2.0 [details in the comments]
Github Repo: https://github.com/hayabhay/whisper-ui
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Self-host Whisper As a Service with GUI and queueing. Schibsted created a transcription service for our journalists to transcribe audio interviews and podcasts really quick.
People may also like this tool which is a bit more about searching the contents. https://github.com/hayabhay/whisper-ui
- Show HN: Self-host Whisper As a Service with GUI and queueing
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Audio equivalent of paperless?
There is whisper ui to create meta data (speech 2 text).
- Whisper-UI: You can now bulk-transcribe, save & search transcriptions from YouTube with OpenAI's Whisper, Streamlit & SQLAlchemy 2.0
- Whisper-UI Update: You can now bulk-transcribe, save & search transcriptions with Streamlit & SQLAlchemy 2.0
FlexGen
- Run 70B LLM Inference on a Single 4GB GPU with This New Technique
- Colorful Custom RTX 4060 Ti GPU Clocks Outed, 8 GB VRAM Confirmed
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Local Alternatives of ChatGPT and Midjourney
LLaMA, Pythia, RWKV, Flan-T5 (self-hosted), FlexGen
- FlexGen: Running large language models on a single GPU
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Show HN: Finetune LLaMA-7B on commodity GPUs using your own text
> With no real knowledge of LLM and only recently started to understand what LLM terms mean, such as 'model, inference, LLM model, intruction set, fine tuning' whatelse do you think is required to make a took like yours?
This was mee a few weeks ago. I got interested in all this when FlexGen (https://github.com/FMInference/FlexGen) was announced, which allowed to run inference using OPT model on consumer hardware. I'm an avid user of Stable Diffusion, and I wanted to see if I can have an SD equivalent of ChatGPT.
Not understanding the details of hyperparameters or terminology, I basically asked ChatGPT to explain to me what these things are:
Explain to someone who is a software engineer with limited knowledge of ML terms or linear algebra, what is "feed forward" and "self-attention" in the context of ML and large language models. Provide examples when possible.
- Could this new flexgen be used in place of GPTq? or is this different?
- OpenAI is expensive
What are some alternatives?
whisper.cpp - Port of OpenAI's Whisper model in C/C++
llama - Inference code for Llama models
whisper - Robust Speech Recognition via Large-Scale Weak Supervision
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
transcribe-anything - Input a local file or url and this service will transcribe it using Whisper AI. Completely private and Free 🤯🤯🤯
text-generation-inference - Large Language Model Text Generation Inference
whisper-playground - Build real time speech2text web apps using OpenAI's Whisper https://openai.com/blog/whisper/
nlp
DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
audio-files-addon - Audio file support for Docspell
audiolm-pytorch - Implementation of AudioLM, a SOTA Language Modeling Approach to Audio Generation out of Google Research, in Pytorch