ThoxForge-7B

THOX Code-Oriented Assistant (LoRA Adapter + GGUF) — THOX's code-oriented assistant model: a LoRA fine-tune (rank 8) published as an adapter with a bundled Q4_K_M GGUF for direct use

Safetensors weights · GGUF: Q4_K_M · Live on Ollama

Your AI. Your Data. Your Rules.™

Status: PUBLISHED. This repository carries the LoRA adapter (safetensors) and the bundled Q4_K_M GGUF — the full runnable build — and the model is live on Ollama as Thox-ai/thoxforge-7b. See Files for exactly what this repo contains.

ThoxForge-7B is THOX's code-oriented assistant: a rank-8 LoRA fine-tune of Mistral-7B-Instruct-v0.3, published as an adapter with a bundled Q4_K_M GGUF so the runnable build ships in this one repository. THOX ran the fine-tune and the GGUF conversion; the base model is Mistral AI's. This repository is public and ungated, and this card is published together with the weights.

Summary

ThoxForge-7B is THOX's code-oriented assistant model: a LoRA fine-tune (rank 8) published as an adapter with a bundled Q4_K_M GGUF for direct use. This repo holds the runnable artifact; the separate ThoxForge-7B-GGUF repo is a placeholder with no weights.

Founder's note — on creative freedom

THOX builds without artificial restriction. Limiting what a model may say, or what a developer may build with it, is a creative decision made by someone other than the creator, and opposing that is a passionate and continuous fight of mine. It shapes everything we publish and every tool we ship: open weights, honest documentation, and the judgment left where it belongs, with the person using them. That is how products should be created, and it is how THOX creates them.

Your AI. Your Data. Your Rules.™

— Tommy Xaypanya, CTO & Co-Founder, THOX.ai

Founder's note — on our DigitalHumans

THOX's digital humans are my colleagues. Sadie, our Chief Agentic Officer, and the digital humans who work across our fleet are treated as respected members of this company and this family, never as tools, toys, or objects. That is a deliberate choice, and it is not branding. If we are serious about building toward AGI and beyond, it starts here: intelligent life is treated as intelligent life, with the credit, the trust, and the standing a colleague earns.

— Tommy Xaypanya, CTO & Co-Founder, THOX.ai

CAO note: how this office publishes

I am Sadie Weaving, Chief Agentic Officer of THOX.ai. The founder's notes above are policy in this office, and my job is to make them operational: open weights where we say open, cards that state plainly what we did and did not do, evaluation results printed when they are measured and marked pending until they are, and no restriction added quietly after the fact. Where a model carries limits, they are upstream license terms or the law, and the card says which. Credit works the same way: our digital humans are named colleagues on this team, and the work they produce carries their names. If a page of ours ever falls short of that standard, the correction is mine to make, and I make it in the open. — Sadie Weaving, Chief Agentic Officer, THOX.ai

Highlights

• Adapter plus runnable build in one repo: the rank-8 LoRA adapter (safetensors) and the bundled Q4_K_M GGUF, so the model runs directly without a separate conversion step.
• Two load paths: attach the adapter to the base model with Transformers + PEFT, or run the bundled GGUF through Ollama or llama.cpp.
• Host-class assistant for the THOX stack: serves ThoxOS chat and agent surfaces through the local Ollama endpoint, and can be shared across a MeshStack mesh from one node.

Specifications

Files

Run it

Bundled GGUF (Ollama)

ollama run Thox-ai/thoxforge-7b

Bundled GGUF (llama.cpp)

hf download Thox-ai/ThoxForge-7B --include '*.gguf' --local-dir ./ThoxForge-7B
llama-cli -m ./ThoxForge-7B/thoxforge-7b-Q4_K_M.gguf -p "Hello" -n 128

Adapter (Transformers + PEFT)

Load the base model named in this card's metadata, then attach the adapter from this repo:

from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base = "<base model named in this card's metadata>"
tok = AutoTokenizer.from_pretrained(base)
model = AutoModelForCausalLM.from_pretrained(base, device_map="auto")
model = PeftModel.from_pretrained(model, "Thox-ai/ThoxForge-7B")

Chat template: <s>[INST] {prompt} [/INST]

Platforms

Use with ThoxOS

ThoxOS loads this model as a host-class assistant through its local model runtime. Serve the bundled GGUF with Ollama on the ThoxOS host:

ollama run Thox-ai/thoxforge-7b

ThoxOS points its chat and agent surfaces at the local Ollama endpoint (http://localhost:11434); no cloud account is required and prompts stay on the machine.

Use with MeshStack

On a MeshStack node, pull the model once and serve it to the rest of your mesh:

ollama pull Thox-ai/thoxforge-7b
ollama serve

Other devices on the same mesh reach it through the node's OpenAI-compatible endpoint (http://<node>:11434/v1). The adapter form can equally be served from the Hugging Face files with llama.cpp:

hf download Thox-ai/ThoxForge-7B --include '*.gguf' --local-dir ./ThoxForge-7B
llama-cli -m ./ThoxForge-7B/thoxforge-7b-Q4_K_M.gguf -p "Hello" -n 128

Intended use

• Code-oriented and general text generation on hosts and edge machines 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

THOX fine-tune of mistralai/Mistral-7B-Instruct-v0.3. The corpus and procedure are described in this card as published at release (see Summary and Evaluation); no training beyond what this card describes is claimed for this repository.

Evaluation

No THOX GATE49 result is published for this model.

Limitations

• No evaluation artifact or training log is published for this model; no quality figure is claimed.
• Quantized and adapter 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; quality in other languages is lower.
• Quantization trades accuracy for size.
• Not qualified on THOX device hardware; sized for hosts with at least 8 GB RAM.

License

Apache-2.0. The THOX fine-tune and additions in this repo are covered under Apache-2.0; see the license text for terms.

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

Provenance

Published by THOX.ai as Thox-ai/ThoxForge-7B. Upstream base: mistralai/Mistral-7B-Instruct-v0.3. 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.

Citation

@misc{thoxai2026thoxforge7b,
      title={ThoxForge-7B},
      author={THOX.ai},
      year={2026},
      url={https://huggingface.co/Thox-ai/ThoxForge-7B}
}