thox-micro-125m

From-Scratch THOX Base Model — a THOX-owned base/completion model trained from scratch: a 123M-parameter decoder for edge and on-device use

Safetensors weights · GGUF: Q4_0, Q4_K_M, thox-micro-125m.f16.gguf

Your AI. Your Data. Your Rules.™

Status: PUBLISHED — RESEARCH MODEL. A THOX-owned base/completion model trained from scratch (123M-parameter decoder) for edge and on-device use. See Files for exactly what this repo contains.

Summary

thox-micro-125m is a THOX-owned base/completion model trained from scratch: a 123M-parameter decoder for edge and on-device use. It is not an instruction-tuned assistant; for the chat build, see Thox-ai/thox-micro-125m-instruct. GGUF builds are bundled in this repo (Q4_0, Q4_K_M, F16) and in Thox-ai/thox-micro-125m-GGUF.

Highlights

• thox-micro-125m is a THOX-owned base/completion model trained from scratch: a 123M-parameter decoder for edge and on-device use.
• python from transformers import AutoModelForCausalLM, AutoTokenizer tok = AutoTokenizer.from_pretrained("Thox-ai/thox-micro-125m") model = AutoModelForCausalLM.from_pretrained("Thox-ai/thox-micro-125m") bash ollama run hf.co/Thox-ai/thox-micro-125m:Q4_K_M

Specifications

Files

Architecture

Run it

from transformers import AutoModelForCausalLM, AutoTokenizer
tok = AutoTokenizer.from_pretrained("Thox-ai/thox-micro-125m")
model = AutoModelForCausalLM.from_pretrained("Thox-ai/thox-micro-125m")

ollama run hf.co/Thox-ai/thox-micro-125m:Q4_K_M

Platforms

Intended use

• On-device and edge text completion within the THOX stack.
• Not a safety-aligned public assistant unless deployed behind THOX guardrails.
• Out of scope: medical, legal, financial, safety-critical, or other high-stakes decisions without human review; unattended control of physical devices without a confirmation step.

Training data and procedure

Trained by THOX from scratch as part of the THOX small-model research line. The corpus and procedure are as described in this card at release; no external base model was used.

Evaluation

Best validation loss 2.6099. No THOX GATE49 result is published for this model.

Limitations

• A small base model: completion-style behaviour, weak factual reliability; verify important answers.
• Behaviour and bias reflect the training data, which is mostly English; quality in other languages is lower.
• Quantization trades accuracy for size; lower-bit files degrade more.

License

Apache-2.0. Trained from scratch by THOX.ai LLC; covered under Apache-2.0.

THOX.ai — Your AI. Your Data. Your Rules.™

Provenance

Published by THOX.ai as Thox-ai/thox-micro-125m. THOX from-scratch research line; no upstream base model. This card was conformed to THOX Model Card Standard v1.0 on 2026-10-31 (frontmatter, tags, header, files, and section structure); the technical content is as published at release.

Research

Weight-Space Programming for THOX Edge Models: Evidence Review, Small-Scale Recreation, and a Signed Patch Channel

THOX.ai Research technical report v1.1.0, 4 November 2026. Craig Ross and Tommy Xaypanya, THOX.ai LLC. DOI: https://doi.org/10.5281/zenodo.23955394 — Paper page: https://thox.ai/research/papers/weight-space-programming — PDF: https://huggingface.co/datasets/Thox-ai/thox-whitepapers/resolve/main/weight-space-programming/Weight-Space-Programming-for-THOX-Edge-Models_v1.1.0.pdf

The paper names thox-micro-125m as its in-house target: trained by THOX from scratch, a weight-space patch here would be the first fully THOX-owned artifact of the program if the paper's gates pass. Its loop baseline is part of the paper's pre-registered Section 5 protocol; the paper claims no weight-space result for this model.

Citation

@misc{thoxai2026thoxmicro125m,
      title={thox-micro-125m},
      author={THOX.ai},
      year={2026},
      url={https://huggingface.co/Thox-ai/thox-micro-125m}
}