thox-micro-125m

thox-micro-125m

Your AI. Your Data. Your Rules.

From-scratch 123M Llama-architecture base/completion model for edge and on-device use.

What this is

• Trained from scratch (THOX-owned) — Apache-2.0.
• Base/completion model, not an instruction-tuned assistant.
• Best validation loss 2.6099 (internal eval).

Architecture (from config)

Intended use

On-device / edge text generation within the THOX stack. Not a safety-aligned public assistant unless deployed behind THOX guardrails.

Usage

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

Links

• GGUF: Thox-ai/thox-micro-125m-GGUF
• Docs: https://docs.thox.ai

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THOX.ai LLC — Your AI. Your Data. Your Rules. · On-device and private by design.

Temporary demo Space: tommytracx/thox-micro-125m-Space (org Space paused on quota).

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Files

Use with ThoxOS

Download the file once and run it fully offline on a ThoxOS host (or any Linux/macOS/Windows machine):

pip install -U "huggingface_hub[cli]"
hf download Thox-ai/thox-micro-125m thox-micro-125m.Q4_K_M.gguf --local-dir ./thox-micro-125m
llama-cli -m ./thox-micro-125m/thox-micro-125m.Q4_K_M.gguf -p "Hello" -n 128

Ollama (pulls straight from the Hub):

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

LM Studio: search Thox-ai/thox-micro-125m in the model browser (or lms get Thox-ai/thox-micro-125m), pick thox-micro-125m.Q4_K_M.gguf, and load it.

Use with MeshStack

Serve the model as an OpenAI-compatible endpoint on any MeshStack node, then register that endpoint with your MeshStack coordinator (protocol openai, base URL http://<node-ip>:8080/v1; or protocol ollama at http://<node-ip>:11434 if you serve it with Ollama).

llama-server -m ./thox-micro-125m/thox-micro-125m.Q4_K_M.gguf --host 0.0.0.0 --port 8080 -c 4096
curl http://<node-ip>:8080/v1/chat/completions -H 'Content-Type: application/json' \
  -d '{"messages":[{"role":"user","content":"Hello"}]}'

Device fit (by file size only)

• thox-micro-125m.Q4_0.gguf (81.32 MB): Small (<600 MB): single-board computers with ≥1 GB RAM, phones, any laptop/desktop.
• thox-micro-125m.Q4_K_M.gguf (84.66 MB): Small (<600 MB): single-board computers with ≥1 GB RAM, phones, any laptop/desktop.
• thox-micro-125m.f16.gguf (248.99 MB): Small (<600 MB): single-board computers with ≥1 GB RAM, phones, any laptop/desktop.

RAM needed ≈ file size + context (KV cache) + runtime overhead. These tiers are derived from file size alone; no throughput, TOPS or battery figures are claimed here.

Licence and attribution

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

Out of scope

• Medical, legal, financial, safety-critical or other high-stakes decisions without human review.
• Unattended control of physical devices or actuators without a confirmation step.
• Any use prohibited by the upstream licence or acceptable-use policy.

Limitations and bias

• Small and quantized models make factual mistakes and can produce confident but wrong output; verify important answers.
• Behaviour and bias reflect the training data, which is mostly English web/instruction text; quality in other languages is lower unless stated above.
• Quantization trades accuracy for size; lower-bit files degrade more.

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THOX.ai LLC — Your AI. Your Data. Your Rules.™ · thox.ai · Contact: [email protected]

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