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AbstractPhil
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AI & ML interests

datasets, research papers, experimentation, vision, classification, text encoders, tokenization, llms, diffusion, distillation, and more.

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updated a model about 1 hour ago
AbstractPhil/alephllm-mini-beatrix-training
repliedto their post about 6 hours ago
My apologies for the incorrect format for the AMOE arms from the experimental branch. They have been saving as torch objects. They are now correctly saving as safetensors format. My apologies for the inconvenience this may cause for you use. I will be modifying the codespaces to use the correct safetensors formats. After the first 20.9b tokens trained, the real experiments begins. Beatrix V3's first prepped-state modular command structure has been attached for dynamic training. These arms will exist as appendages for Beatrix - trained alongside with the trunk until the end of the run. These exist for experimental extraction, analysis, distillation experiments, memory experiments, mathematics experiments, and more. Each arm will be built along the chain for specific test cases. Expectation for each is already lined up and the outcomes are tested for, but the model still may face instability and must be monitored. As her first arm learns tinystories, she builds direct composite semantic structure throughout this system. Think of it like, the first higher-functioning cognition attachment. She's still very naΓ―ve and structurally unaware, so attaching new limbs is essentially extending a structure that is not yet finished forming. Nothing but fragments of issued information from an unknown source. In this case, this structure has been tested hundreds of times to ensure she will not simply collapse during training by having this attached.
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