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#thecompaniesapi big LLM results from our pipeline now gets saved as json files to prepare datasets for our own models ; optimizing the queue does not seem to be a finite task
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start first trainigng with Flux on GPU again now with bigger HDD #photoai
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install LM Studio and get TheBloke's latest LLMs to try new 40x GPU cores #life
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#thecompaniesapi early LLM results are bonkers but the qop/s are relatively slow; setting up results storage to train smaller models; one step at a time
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got actually working dataset for clv #ml4all
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provision batch of L4 and L40S GPUs at Scaleway for #mirage since our account got validated and quotas lifted
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Work on #nichewit, pull in production datasets to iterate bit faster locally
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finish migrating #mirage kubernetes intel and nvidia gpu instances to scaleway, getting last-generation NVIDIA L40S + L4 GPUs, running much smoother now! (previously: old A40 and A16)
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#thecompaniesapi work on datasets filtering & classification UI ; we can now review outputs from Claude/GPT and directly grab the dataset to send for fine-tuning
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setup more powerful vm for processing data & training models #mused
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Updating Automatic 11, Installing a new video gpu, today its a day to learn how to train local models :B #dailywork
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Learn about AWS Sagemaker and spin up a beastly GPU instance to do deep learning training #guard
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Chunk dataset big files and import to DB (Data Science project) #zg
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Finally make breakthrough with CUDA optimizing work and bring generation time down from ~30 mins to ~1min
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generate my first images with Stable Diffusion 2.0 + Dreambooth on my own GPU VPS #avatarai
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start building dongle for new GPU API so we can go from $10 to $1 per render and increase margins from 75% to 97.5% and try more new features #avatarai
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#thecompaniesapi subdomains support ready for merge ; swap efforts back on AI to start creating the datasets ; added new extractions steps last missing main table datapoints, we can now fill all our columns with combination of website + ai extraction! next step fine tuning
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start first training with Flux on GPU #photoai
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Prepare datasets for demo
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study Stanford’s Alpaca instruction model finetuning for LLaMA source data #life
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