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beta model running #s2c
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test different models #avatarai
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Read [Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters](arxiv.org/pdf/2408.03314)
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keep improving training DB for gpt-fine-tuning #reva
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create training set for gpt-3 fine tuning #reva
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test FAL.ai with different params #photoai
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play with system prompts and chatGPT API to see if we can replace fine-tuned model #reva
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change fine tuning strategy and data structure and play with new fine tuned model #reva
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continue experimenting with different models #ai
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generate models #scribers
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Trained a basic flux lora model on replicate… need more fine tuning tbh #nbpai
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Finally played with FLUX to create AI models and then generated try-ons with #fashn model
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Switched all low-fidelity AI tasks model from 3.5-turbo to the newest gpt-4o-mini. #retently
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Added new GPT model to #opentranslate
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testing with 3d model generator
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Fix fast LLM model failing with Error 400 and add a fallback to other model in case it errors #jobician
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try new noise model #photoai
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cross 200k on replicate with my model used in #audiogest #spectropic
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add GPT_CUSTOM function to customize top_n, model, temperature for requests on cell level #docgptai
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