gpjt
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- Building intuition about LLM parameter counts (gilesthomas.com)
- Poppy the training box, part 1: the beginnings (gilesthomas.com)
- From bigrams to GPT-2, one component at a time (in Jax) (gilesthomas.com)
- Building a Jax training loop for an LLM training run (gilesthomas.com)
- Thoughts on Role Confusion (gilesthomas.com)
- Flax debugging: making a hash of things (gilesthomas.com)
- 10Gb/s Ethernet: switching to a Broadcom SFP+ module (gilesthomas.com)
- Jax: Commitment Issues (gilesthomas.com)
- Jax Back Ends and Devices (gilesthomas.com)
- Using Safetensors with Flax (gilesthomas.com)
- First Looking into Jax (gilesthomas.com)
- 10Gb/s Ethernet: using mini-heatsinks with a 10GBASE-T SFP+ module (gilesthomas.com)
- 10Gb/s Ethernet: what I did to get it working in my home (gilesthomas.com)
- 10Gb Ethernet: what I had to (re)learn (gilesthomas.com)
- LLM from scratch, part 33 – what I learned from the appendices (gilesthomas.com)
- How an LLM becomes more coherent as we train it (gilesthomas.com)
- LLM from scratch, part 32k – Interventions: gradient accumulation (gilesthomas.com)
- Provision: LLM-powered server setup from Markdown (provision.sh)
- LLM from scratch, part 32j – trying to train a better model in the cloud (gilesthomas.com)
- Writing an LLM from scratch, part 32h – Interventions: full fat float32 (gilesthomas.com)
- Writing an LLM from scratch, part 32g – Interventions: weight tying (gilesthomas.com)
- Writing an LLM from scratch, part 32f – Interventions: weight decay (gilesthomas.com)
- Writing an LLM from scratch, part 32e – Interventions: the learning rate (gilesthomas.com)