Instructions to use rotextechnologiesuk/nuclear-sqep with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use rotextechnologiesuk/nuclear-sqep with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="rotextechnologiesuk/nuclear-sqep",
	filename="rotex_nuclear_sqep_Q4_K_M.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use rotextechnologiesuk/nuclear-sqep with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf rotextechnologiesuk/nuclear-sqep:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf rotextechnologiesuk/nuclear-sqep:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf rotextechnologiesuk/nuclear-sqep:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf rotextechnologiesuk/nuclear-sqep:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf rotextechnologiesuk/nuclear-sqep:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf rotextechnologiesuk/nuclear-sqep:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf rotextechnologiesuk/nuclear-sqep:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf rotextechnologiesuk/nuclear-sqep:Q4_K_M

Use Docker

docker model run hf.co/rotextechnologiesuk/nuclear-sqep:Q4_K_M

LM Studio
Jan

vLLM

How to use rotextechnologiesuk/nuclear-sqep with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "rotextechnologiesuk/nuclear-sqep"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "rotextechnologiesuk/nuclear-sqep",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/rotextechnologiesuk/nuclear-sqep:Q4_K_M

Ollama
How to use rotextechnologiesuk/nuclear-sqep with Ollama:
```
ollama run hf.co/rotextechnologiesuk/nuclear-sqep:Q4_K_M
```

Unsloth Studio

How to use rotextechnologiesuk/nuclear-sqep with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for rotextechnologiesuk/nuclear-sqep to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for rotextechnologiesuk/nuclear-sqep to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for rotextechnologiesuk/nuclear-sqep to start chatting

How to use rotextechnologiesuk/nuclear-sqep with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf rotextechnologiesuk/nuclear-sqep:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "rotextechnologiesuk/nuclear-sqep:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use rotextechnologiesuk/nuclear-sqep with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf rotextechnologiesuk/nuclear-sqep:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default rotextechnologiesuk/nuclear-sqep:Q4_K_M

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use rotextechnologiesuk/nuclear-sqep with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf rotextechnologiesuk/nuclear-sqep:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "rotextechnologiesuk/nuclear-sqep:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Docker Model Runner
How to use rotextechnologiesuk/nuclear-sqep with Docker Model Runner:
```
docker model run hf.co/rotextechnologiesuk/nuclear-sqep:Q4_K_M
```

Lemonade

How to use rotextechnologiesuk/nuclear-sqep with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull rotextechnologiesuk/nuclear-sqep:Q4_K_M

Run and chat with the model

lemonade run user.nuclear-sqep-Q4_K_M

List all available models

lemonade list

nuclear-sqep / README.md

rotextechnologies

Update README.md

8d0cc54 verified about 2 months ago

preview code

Raw

History Blame Contribute Delete

13.6 kB

	---
	license: other
	license_name: model-public-preview-licence-v1.0
	license_link: https://huggingface.co/rotextechnologies/nuclear-sqep/blob/main/license.md
	language:
	- en
	tags:
	- gguf
	- q4_k_m
	- public-preview
	- evaluation
	- ai
	- engineering
	- technical-consultancy
	- industrial-ai
	- nuclear
	- nuclear decommissioning
	- nuclear new building
	- small modular reactor
	pipeline_tag: text-generation
	library_name: llama.cpp
	datasets: []
	metrics: []
	---

	> ⚠️ PUBLIC PREVIEW — NOT OPEN SOURCE. This is a controlled evaluation release. Commercial use, hosted inference, derivative model creation, fine-tuning, distillation, and redistribution are not permitted without a separate written commercial licence from Rotex Technologies Ltd. See [license.md](./license.md).

	---

	# nuclear-sqep — Public Preview GGUF Model

	## 1. Executive Summary

	nuclear-sqep is a public preview GGUF release developed by Rotex Technologies Ltd — a UK-based digital manufacturing, engineering services specialising in CFD, FEA, and technical consultancy across the nuclear, aerospace, automotive, marine, wind, solar, energy storage, and oil & gas sectors.

	This release provides a Q4_K_M quantised model intended to demonstrate the capability of our wider commercial model family, whilst preserving our proprietary full‑precision weights, training pipeline, domain‑specific datasets, and deployment optimisations.

	### ✅ This model is suitable for:
	- Local, offline evaluation and experimentation
	- Technical benchmarking against publicly reported metrics
	- Early-stage customer and partner feedback
	- Investor and technical due diligence
	- Edge and air-gapped inference testing
	- Academic and industry technical review

	### ❌ This model is not licensed for:
	- Commercial deployment or production use
	- Hosted inference, SaaS, or API services
	- Fine‑tuning, distillation, or adapter training
	- Derivative model creation of any kind
	- Redistribution at scale or mirroring
	- Use as a component in a competing product or service

	For commercial access, evaluation under NDA, or partnership discussions, contact:
	📧 [sales@rotextechnologies.com](mailto:sales@rotextechnologies.com)


	## 2. Why This Model Exists

	Most current models in this parameter class are either:
	- too large for practical edge and offline deployment;
	- too generic for specialist industrial and engineering use;
	- costly to host and difficult to validate in regulated environments;
	- trained on data of unknown provenance, creating unacceptable IP and compliance risk;
	- unsuitable for controlled, auditable engineering workflows.

	Rotex Technologies Ltd is building a model family focused on:

	- Domain precision — trained and evaluated on corpora, from 400+ curated technical and engineering literature, focusing in the UK nuclear sector;
	- Deployability — designed for edge, air-gapped, and resource-constrained environments from the outset;
	- Auditability — built for workflows where traceability, provenance, and controlled outputs matter;
	- Data security and privacy — fully air-gapped development pipeline; all processes, from raw document ingestion to model build, are isolated from the internet, ensuring complete confidentiality of datasets and training corpora;
	- Commercial clarity — a transparent licensing model that respects both open evaluation and proprietary IP.

	This public preview is the first release in our production model pipeline — a controlled, quantised snapshot sufficient for meaningful technical evaluation without compromising our proprietary training assets, architecture, or development IP.


	## 3. Target Audience

	This preview is intended for:

	\| Audience \| Purpose \|
	\|---\|---\|
	\| Technical evaluators \| Assess model capability, quality, and behaviour \|
	\| Engineering teams \| Test domain-specific performance on representative tasks \|
	\| Enterprise innovation groups \| Evaluate fit within controlled internal workflows \|
	\| Investors & due diligence teams \| Conduct independent technical assessment \|
	\| Research partners \| Explore collaboration potential \|
	\| Early design partners \| Inform commercial roadmap and integration requirements \|

	It is not intended for, and not licensed for, production deployment of any kind.

	## 4. Model Details

	\| Field \| Detail \|
	\|---\|---\|
	\| Model name \| rotex_nuclear_sqep \|
	\| Release type \| Public preview (evaluation only) \|
	\| File format \| GGUF \|
	\| Quantisation \| Q4_K_M \|
	\| Primary language \| English \|
	\| Domain focus \| Engineering, technical consultancy, industrial applications \|
	\| Release date \| 26 May 2026 \|
	\| Pipeline position \| v1.0 — first production release; higher-precision variants (BF16, Q8_0) available to qualified commercial customers \|
	\| Licence \| Model Public Preview Licence v1.0 \|
	\| Commercial use \| Not permitted without written licence from Rotex Technologies Ltd \|
	\| Developer \| Rotex Technologies Ltd, United Kingdom \|


	## 5. What Is Included — and What Is Not

	### ✅ Public in this release:
	- Q4_K_M GGUF model file
	- Inference instructions for llama.cpp and compatible runtimes
	- Evaluation prompts and example outputs
	- Safety, limitation, and known-issue notes
	- Public benchmark summary
	- Full licence terms and acceptable use policy

	### ❌ Not included in this release:
	- Higher-precision model variants (BF16)
	- Higher-quality quantisations (Q8_0)
	- Training, fine‑tuning, or alignment datasets
	- Fine‑tuning recipes, hyperparameters, or training code
	- Internal evaluation harness and proprietary benchmarks
	- Commercial deployment configuration and system prompts
	- Domain‑specific commercial variants
	- Any component that would enable derivative model creation

	## 6. Permitted & Prohibited Uses

	### ✅ Permitted (subject to licence terms):
	- Local, non‑commercial evaluation and experimentation
	- Technical benchmarking and comparison
	- Academic and industry review and publication of fair results
	- Internal proof‑of‑concept assessment
	- Investor and partner due diligence

	### ❌ Prohibited (without separate written commercial licence):
	- Production deployment of any kind
	- Commercial use, revenue generation, or cost reduction
	- SaaS, API, or hosted inference services
	- Fine‑tuning, distillation, merging, or adapter creation
	- Training or improving any other model (competing or otherwise)
	- Redistribution, mirroring, or repackaging at scale
	- Any use violating the [Acceptable Use Policy](./ACCEPTABLE_USE_POLICY.md)

	Full terms: [license.md](./license.md)


	## 7. Quick Start

	### Prerequisites
	- [llama.cpp](https://github.com/ggerganov/llama.cpp) (built with GPU acceleration recommended)
	- Or any GGUF-compatible runtime (Ollama, LM Studio, etc.)

	### Basic inference with llama.cpp

	```bash
	# Download the model file from this repository
	# Then run:

	./llama-cli \
	-m rotex_nuclear_sqep_p2_q4_k_m.gguf \
	-p "Explain the key technical considerations for fatigue analysis in pressure vessel design." \
	-n 512 \
	--temp 0.6 \
	--ctx-size 2048
	```

	### Interactive mode

	```bash
	./llama-cli \
	-m rotex_nuclear_sqep_p2_q4_k_m.gguf \
	--interactive \
	--temp 0.6 \
	--ctx-size 2048
	```

	### With Ollama

	Create a `Modelfile`:

	```dockerfile
	FROM ./rotex_nuclear_sqep_p2_q4_k_m.gguf
	```

	Then:

	```bash
	ollama create nuclear-sqep-preview -f Modelfile
	ollama run nuclear-sqep-preview
	```

	### Suggested evaluation prompts

	```
	"Summarise the key failure modes of a welded joint in cooling water pipes under cyclic thermal loading."

	"Outline the regulatory pathway for nuclear safety case submissions under UK ONR guidance."

	"Explain the 'Justification' process for new nuclear practices in the UK under the JoPIIRR 2004 regulations. Why does the 2025 Regulatory Review argue that this process currently acts as a technical bottleneck for first-of-a-kind (FOAK) designs?"
	```


	## 8. Evaluation & Benchmarking

	We encourage independent benchmarking and technical review. When publishing results:

	- ✅ Attribute the model as: "nuclear-sqep by Rotex Technologies Ltd, used under the Model Public Preview Licence v1.0."
	- ✅ Be transparent about your evaluation methodology, prompt format, and sampling parameters.
	- ✅ Publish both strengths and limitations.
	- ❌ Do not imply endorsement, partnership, or certification by Rotex Technologies Ltd.
	- ❌ Do not disclose any information that would enable reverse engineering or derivative model creation.
	- ❌ Do not use model outputs to train or improve competing models.

	### Suggested evaluation dimensions

	\| Dimension \| Relevance \|
	\|---\|---\|
	\| Domain accuracy \| Factual correctness on engineering and technical queries \|
	\| Instruction following \| Adherence to structured technical prompts \|
	\| Safety & refusal \| Appropriate handling of hazardous or regulated queries \|
	\| Hallucination rate \| Propensity to generate plausible but incorrect technical statements \|
	\| Latency & throughput \| Inference speed on representative edge hardware \|
	\| Quantisation quality \| Comparative performance vs. higher-bit quantisations (available commercially) \|

	We welcome feedback on evaluation methodology, benchmark design, and domain coverage at:
	📧 [info@rotextechnologies.com](mailto:info@rotextechnologies.com)


	## 9. Known Limitations

	As a public preview Q4_K_M quantised model, nuclear-sqep has the following known limitations:

	- Quantisation degradation — Q4_K_M quantisation intentionally reduces fidelity compared to our full‑precision commercial models. Expect some degradation on nuanced technical reasoning and numerical precision.
	- No production safety guarantees — This model has not undergone production safety alignment, red‑teaming, or adversarial robustness testing at commercial grade.
	- Domain coverage — The model's knowledge reflects its training distribution. It may perform less well on topics outside engineering and technical domains.
	- Hallucination — Like all large language models, nuclear-sqep may generate plausible but factually incorrect output. Never rely on model output for safety‑critical decisions without independent verification.
	- No regulatory approval — This model has not been assessed or approved by any regulatory body (UK ONR, HSE, EA, NDA, etc.) for use in safety‑critical or regulated applications.
	- Language — Optimised for English. Performance in other languages is untested and may be unreliable.
	- Context — The model is focused on UK nuclear sector applications and IAEA-aligned safety principles. Adaptation for other jurisdictions or regulated industries is available on request.

	This model is an evaluation artefact. It is not a production‑ready, safety‑assured product.


	## 10. Safety & Responsible Disclosure

	We take safety concerns seriously. If you discover:

	- Generation of hazardous, dangerous, or illegal content
	- Instructions that could cause physical harm
	- Bypass of safety guardrails
	- Biased, discriminatory, or harmful outputs
	- Vulnerabilities that could be exploited
	- Copyright or IP concerns in model outputs

	Please report responsibly to:
	📧 [info@rotextechnologies.com](mailto:info@rotextechnologies.com)

	We commit to acknowledging reports within 5 working days and providing a substantive response within 20 working days. We request a 90‑day embargo before public disclosure of vulnerabilities to allow for assessment and mitigation.

	Do not use this model to generate, distribute, or facilitate content that would violate applicable laws in the United Kingdom, European Union, United States, People's Republic of China, or any other relevant jurisdiction.


	## 11. Citation

	If you reference nuclear-sqep in academic or technical publications:

	```bibtex
	@software{rotex_nuclear-sqep_2026,
	author = {{Rotex Technologies Ltd}},
	title = {nuclear-sqep — Public Preview GGUF Model},
	year = {2026},
	publisher = {Rotex Technologies Ltd},
	url = {https://huggingface.co/rotextechnologies1/nuclear-sqep},
	note = {Model Public Preview Licence v1.0. Q4_K_M quantisation.}
	}
	```

	Suggested in-text attribution:
	"nuclear-sqep by Rotex Technologies Ltd, used under the Model Public Preview Licence v1.0."


	## 12. Commercial Access

	This public preview is not licensed for commercial use. Our commercial offering includes:

	- Higher-precision (BF16) and higher-quality quantised (Q8_0) model variants
	- Domain‑specific fine‑tuned variants
	- Commercial deployment licence
	- SLAs, support, and integration assistance
	- Access to proprietary evaluation tooling
	- Custom development and bespoke model adaptation

	For commercial enquiries, partnership discussions, or evaluation under NDA:
	📧 [sales@rotextechnologies.com](mailto:sales@rotextechnologies.com)
	🌐 [www.rotextechnologies.com](https://www.rotextechnologies.com)

	See [COMMERCIAL_USE.md](./COMMERCIAL_USE.md) for more detail.


	## 13. Repository Documents

	\| Document \| Description \|
	\|---\|---\|
	\| [license.md](https://huggingface.co/rotextechnologiesuk/nuclear-sqep/blob/main/license.md) \| Full legal terms — Model Public Preview Licence v1.0 \|
	\| [ACCEPTABLE_USE_POLICY.md](./ACCEPTABLE_USE_POLICY.md) \| Acceptable use policy and prohibited use categories \|
	\| [COMMERCIAL_USE.md](./COMMERCIAL_USE.md) \| Commercial licensing pathway and FAQ \|

	---

	© Rotex Technologies Ltd. All rights reserved. Rotex Technologies Ltd is a company registered in England and Wales.