Mukhtiar Ali

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https://mokhtiarali.github.io

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updated a Space 6 days ago

MINT-SDSU/CLIP-CC-Bench-Leaderboard

new activity 8 days ago

MINT-SDSU/CLIP-CC:[bot] Conversion to Parquet

reacted to Felladrin's post with 👍 12 days ago

I've open-sourced the trainer I've been using to build tiny language models from scratch, together with the 95M base model I trained with it. The trainer runs on Deno (https://deno.com, cross-platform), trains on WebGPU, and it writes GGUF directly. No Python/PyTorch. The weights live in a GGUF file from the first step to the last, so every checkpoint is already something llama.cpp can load. The model is https://huggingface.co/Felladrin/Minueza-3-95M-Base: 94.7M parameters, 1.95B tokens seen, 8192 context. And here’s the repository on GitHub: https://github.com/felladrin/gguf-trainer Here on Hugging Face, I published the optimizer state next to the weights, so you can continue the pretraining instead of starting over. Or start your own from nothing: `deno run -A cli.ts demo` trains a tiny one end to end in under a minute. And the docs are written for coding agents, so you can point your agent of choice at the GitHub repo and have it drive the whole pipeline.

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