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anudit/
gpt-s2-5m-wgsl

Name: gpt-s2-5m-wgsl
Availability: InStock

AxiomicLabs/GPT-S2-5M

quantized

mit

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GPT-S2-5M — WebGPU / WGSL assets

Runtime assets for running AxiomicLabs/GPT-S2-5M (a 9-layer custom GPTS3 language model) entirely in the browser with hand-written WebGPU (WGSL) compute shaders — no onnxruntime, no WASM inference.

The browser app fetches these files directly from this repo and caches them locally (Cache API), so the ~25 MB download happens only once.

Files

file	used by	notes
`weights.bin`	WGSL engine	all tensors as flat little-endian f32
`manifest.json`	WGSL engine	`{name: {offset, shape}}` index into `weights.bin` + model `config`
`tokenizer.json`, `tokenizer_config.json`, `special_tokens_map.json`	tokenizer	ByteLevel BPE, vocab 4096
`generation_config.json`	reference	bos/eos/pad ids
`model.onnx`, `model.onnx.data`	reference / parity	cache-free full-sequence ONNX export (not used by the WGSL engine)

weights.bin + manifest.json are produced from the source safetensors by scripts/export_weights.py; the ONNX pair by scripts/export_onnx.py.

Use

const BASE = "https://huggingface.co/anudit/gpt-s2-5m-wgsl/resolve/main";
const manifest = await (await fetch(`${BASE}/manifest.json`)).json();
const weights  = await (await fetch(`${BASE}/weights.bin`)).arrayBuffer();
// slice tensors out of `weights` by manifest offsets, upload to WebGPU, run WGSL.

See the source project for the full engine (src/gpts3/*).