A 28M-parameter, pretrained-from-scratch, byte-level agent for tool dispatch. Selection is generable (no fixed-N classifier): a 5-way route head gates modality, a dense two-tower selector scores any tool by its description embedding, and a pointer head copies argument values from the prompt. 50-tool surface. Trained on a corrected, paraphrase-rich + referent- conditioned dataset (danelcsb/localagent-dispatch-data).

Eval (held, disjoint phrasings + slots):

free-form OOD call-name 53% / top-1 56% (45 hand-written queries)
paraphrase-eval selection 63% · referent-conditioned (contextual) selection 72%

Pure PyTorch (no transformers). Load with this repo's LocalAgentLM / ModelConfig.

Files

model.pt / model.safetensors + config.json — checkpoint (backbone + ptr + dense_selector + route_head).
model.fp16.onnx — ONNX graph (logits, hidden) for the in-browser demo.
dispatch_heads.json / heads.json / meta.json — head weights + tokenizer/tool contract.

Demo: https://huggingface.co/spaces/danelcsb/localagent-webgpu · Data: https://huggingface.co/datasets/danelcsb/localagent-dispatch-data · Code: https://github.com/sangbumchoi/localagent

danelcsb/localagent-tiny-30m-byte

LocalAgent — tiny 30M byte-level tool-calling agent

Files

danelcsb/
localagent-tiny-30m-byte