Eg run dreambooth on sd2.1 by tomorrow
OPEN SOURCE
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From Inaccessible to Mainstream: AI Models Now Available to Everyone
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How it started vs How it's going I knew how to recognize exponentials in 2018, but also didn't believe that this was accessible to the median technologist. That is the biggest thing changing with @StabilityAI
; today, hobbyists can run these things on iPhones and CPUs -
LangChain v0.0.35 Release: Documentation Improvements and New Features
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LangChain v0.0.35 Doc improvements @HunterGerlach Fix typing of parameters, flagged by @fcampeot
Expose more parameters for the q&a chains, suggest by @johnjnay Add a `.clear()` method for memory, @shobith and @andrewgleave Support -1 for max_tokens, @BruceHammer -
Setting Up Independent GPU Server Infrastructure for AI
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set up my own GPU server now re: iterate on lesson, don't depend on APIs too much
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Best Linux Distribution for GPU Server Running Stable Diffusion
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Best distro for GPU server to run Stable Diffusion? I'm used to Ubuntu cause my VPS runs it?
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Google Unveils Learning Interpretability Tool and Salience Evaluation Protocol
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Today at 12:30pm the Google booth will host a demo about Google's open source Learning Interpretability Tool (LIT; https://
goo.gle/3kTIiLT) along with a newly introduced evaluation protocol (
https://
goo.gle/3gZSOWl) that illustrates the difference between various salience methods -
LangChain version 0.0.34: OpenAI moderation and fact checking
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LangChain version 0.0.34 Doc cleanup from `moozilla` (if on twitter lmk!) Support for @OpenAI's moderation endpoint LLMFactChecker chain from @thepromptking, original idea by @0xjasper Some more info on the LLM fact checker chain
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GardenMate Wins Call for Code with AI-Driven Food Marketplace
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Ecosystem for Good! Congrats 'GardenMate' Winners #CallForCode tackling #Food #Sustainability with #AI driven #marketplace + people & #tech support! See http://
bit.ly/FoodSDGS #SDGs #agritech #innovation #IBMPartner #data #ML #DataScientist #Python @IBMPartners #OpenSource -
Simple conversation buffer memory with dynamic N adjustment
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it is pretty simple at the moment – just keeps a buffer of the past N conversations in memory. a pretty simple improvement would be dynamically adjusting N based on the length of the conversations
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LangChain Already Supports Conversation Summary Memory
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we actually support that already! https://
langchain.readthedocs.io/en/latest/gett
ing_started/memory.html#ConversationChain-with-ConversationSummaryMemory
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