mini-omni2
Towards Open-source GPT-4o with Vision, Speech and Duplex Capabilities.
https://github.com/gpt-omni/mini-omni2
Towards Open-source GPT-4o with Vision, Speech and Duplex Capabilities.
https://github.com/gpt-omni/mini-omni2
GitHub
GitHub - gpt-omni/mini-omni2: Towards Open-source GPT-4o with Vision, Speech and Duplex Capabilities。
Towards Open-source GPT-4o with Vision, Speech and Duplex Capabilities。 - gpt-omni/mini-omni2
meme_search
Index your memes by their content and text, making them easily retrievable for your meme warfare pleasures. Find funny fast.
https://github.com/neonwatty/meme_search
Index your memes by their content and text, making them easily retrievable for your meme warfare pleasures. Find funny fast.
https://github.com/neonwatty/meme_search
GitHub
GitHub - neonwatty/meme-search: The open source Meme Search Engine. Free and built to self-host locally with Python, Ruby, and…
The open source Meme Search Engine. Free and built to self-host locally with Python, Ruby, and Docker. - neonwatty/meme-search
Async Rate Limiter
Rate limit async requests to API using credits, computation unit per second (CUPS) or request units
https://github.com/Elnaril/credit-rate-limit
Rate limit async requests to API using credits, computation unit per second (CUPS) or request units
https://github.com/Elnaril/credit-rate-limit
GitHub
GitHub - Elnaril/credit-rate-limit: Easily rate limit async requests to API using credits, computation unit per second (CUPS) or…
Easily rate limit async requests to API using credits, computation unit per second (CUPS) or request units, and to those just counting the number of requests per time unit - Elnaril/credit-rate-limit
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meta-llama / llama-stack-apps
Agentic components of the Llama Stack APIs
https://github.com/meta-llama/llama-stack-apps
Agentic components of the Llama Stack APIs
https://github.com/meta-llama/llama-stack-apps
GitHub
GitHub - meta-llama/llama-stack-apps: Agentic components of the Llama Stack APIs
Agentic components of the Llama Stack APIs. Contribute to meta-llama/llama-stack-apps development by creating an account on GitHub.
We're thinking of rewriting our go / java API in python, what do we need to think about?
https://www.reddit.com/r/Python/comments/1gdavp9/were_thinking_of_rewriting_our_go_java_api_in/
https://www.reddit.com/r/Python/comments/1gdavp9/were_thinking_of_rewriting_our_go_java_api_in/
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
You Should Probably Pay Attention to Tokenizers
This article emphasizes the importance of understanding tokenizers in AI applications, particularly for Retrieval-augmented generation (RAG) systems. The author demonstrates how different tokenizers handle various types of text input, including emojis and misspelled words, and explains how tokenization affects embedding quality and overall performance in natural language processing tasks.
https://cybernetist.com/2024/10/21/you-should-probably-pay-attention-to-tokenizers/
This article emphasizes the importance of understanding tokenizers in AI applications, particularly for Retrieval-augmented generation (RAG) systems. The author demonstrates how different tokenizers handle various types of text input, including emojis and misspelled words, and explains how tokenization affects embedding quality and overall performance in natural language processing tasks.
https://cybernetist.com/2024/10/21/you-should-probably-pay-attention-to-tokenizers/
Cybernetist
You Should Probably Pay Attention to Tokenizers
Last week I was helping a friend of mine to get one of his new apps off the ground. I can’t speak much about it at the moment,
other than like most apps nowadays it has some AI sprinkled over …
other than like most apps nowadays it has some AI sprinkled over …
Python Threading Tutorial: Basic to Advanced (Multithreading, Pool Executors, Daemon, Lock, Events)
https://www.reddit.com/r/Python/comments/1gj177a/python_threading_tutorial_basic_to_advanced/
https://www.reddit.com/r/Python/comments/1gj177a/python_threading_tutorial_basic_to_advanced/
Reddit
From the Python community on Reddit: Python Threading Tutorial: Basic to Advanced (Multithreading, Pool Executors, Daemon, Lock…
Explore this post and more from the Python community
PyBay 2024 Videos
The talks from PyBay 2024 are now available online.
https://www.youtube.com/playlist?list=PL85KuAjbN_gvx5b_BgLVcKfccnlZAVPMk
The talks from PyBay 2024 are now available online.
https://www.youtube.com/playlist?list=PL85KuAjbN_gvx5b_BgLVcKfccnlZAVPMk
YouTube
PyBay 2024
PyBay is an annual conference gathering of Pythonistas put on by the Bay Area Python Association. PyBay 2024 was our 9th annual event, held on September 21, ...
From Python to CPU instructions: Part 1
In the first part of a two-part series, we’ll compare the same program written in C and Python to reveal what Python hides from us.
https://dilovan.substack.com/p/from-python-to-cpu-instructions-part
In the first part of a two-part series, we’ll compare the same program written in C and Python to reveal what Python hides from us.
https://dilovan.substack.com/p/from-python-to-cpu-instructions-part
Thoughts on Data
From Python to CPU instructions: Part 1
This post, is what happens, when you get an intrusive thought about how your computer works, in the middle of the night.
Avaiga / taipy
Turns Data and AI algorithms into production-ready web applications in no time.
https://github.com/Avaiga/taipy
Turns Data and AI algorithms into production-ready web applications in no time.
https://github.com/Avaiga/taipy
GitHub
GitHub - Avaiga/taipy: Turns Data and AI algorithms into production-ready web applications in no time.
Turns Data and AI algorithms into production-ready web applications in no time. - Avaiga/taipy
Investigation of a Workbench UI Latency Issue
Netflix engineers investigated a JupyterLab UI latency issue in their Workbench product, tracing it to an unexpected interaction between a resource usage extension and memory allocation. The root cause was identified as the extension's performance degrading linearly with increased virtual memory usage, despite available physical memory.
https://netflixtechblog.com/investigation-of-a-workbench-ui-latency-issue-faa017b4653d
Netflix engineers investigated a JupyterLab UI latency issue in their Workbench product, tracing it to an unexpected interaction between a resource usage extension and memory allocation. The root cause was identified as the extension's performance degrading linearly with increased virtual memory usage, despite available physical memory.
https://netflixtechblog.com/investigation-of-a-workbench-ui-latency-issue-faa017b4653d
Medium
Investigation of a Workbench UI Latency Issue
By: Hechao Li and Marcelo Mayworm