Instructions to use lerugray/spectre-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use lerugray/spectre-7b with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="lerugray/spectre-7b", filename="spectre-qwen2-5-7b-instruct-Q5_K_M.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use lerugray/spectre-7b 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 lerugray/spectre-7b:Q5_K_M # Run inference directly in the terminal: llama cli -hf lerugray/spectre-7b:Q5_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf lerugray/spectre-7b:Q5_K_M # Run inference directly in the terminal: llama cli -hf lerugray/spectre-7b:Q5_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 lerugray/spectre-7b:Q5_K_M # Run inference directly in the terminal: ./llama-cli -hf lerugray/spectre-7b:Q5_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 lerugray/spectre-7b:Q5_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf lerugray/spectre-7b:Q5_K_M
Use Docker
docker model run hf.co/lerugray/spectre-7b:Q5_K_M
- LM Studio
- Jan
- vLLM
How to use lerugray/spectre-7b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "lerugray/spectre-7b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lerugray/spectre-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/lerugray/spectre-7b:Q5_K_M
- Ollama
How to use lerugray/spectre-7b with Ollama:
ollama run hf.co/lerugray/spectre-7b:Q5_K_M
- Unsloth Studio
How to use lerugray/spectre-7b 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 lerugray/spectre-7b 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 lerugray/spectre-7b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for lerugray/spectre-7b to start chatting
- Atomic Chat new
- Docker Model Runner
How to use lerugray/spectre-7b with Docker Model Runner:
docker model run hf.co/lerugray/spectre-7b:Q5_K_M
- Lemonade
How to use lerugray/spectre-7b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull lerugray/spectre-7b:Q5_K_M
Run and chat with the model
lemonade run user.spectre-7b-Q5_K_M
List all available models
lemonade list
| license: cc-by-nc-4.0 | |
| base_model: Qwen/Qwen2.5-7B-Instruct | |
| tags: | |
| - text-generation | |
| - register-transfer | |
| - marx | |
| - political-economy | |
| language: | |
| - en | |
| # spectre: a Karl Marx register model | |
| A 7B voice tune that writes in the register of Karl Marx: the political economist, the | |
| theorist of capital, the correspondent who dissected how the bourgeois order actually | |
| works. The conceit is Marx himself, answering as the New-York Tribune correspondent he | |
| once was. A spectre is haunting your VRAM. | |
| **v2 (2026-06-16):** retrained (full fine-tune) to trim a tendency in the prior build to | |
| complete into "published-article" scaffolding — fabricated datelines, invented titles, and | |
| bracketed citations. v2 answers more as a man speaking aloud than as an article for print. | |
| Weights updated in place; same conceit, same public-domain sources. | |
| It channels the analysis, not a biography. The model trains on Marx and Engels's own | |
| voice-bearing works in their public-domain English: the Manifesto, the Eighteenth | |
| Brumaire, Wage-Labour and Capital, Value Price and Profit, The Civil War in France, the | |
| Critique of the Gotha Programme. What it learns is the cadence — the patient exposure of | |
| contradiction, the long argumentative sentence, the contempt for the self-deceiving. | |
| ## What it does | |
| Ask it about labour, capital, the commodity, the state, religion, or the present day and | |
| it answers in the analytical-polemical register. It etymologises the modern through the | |
| nineteenth century: asked about the gig economy it reaches for the horse-cart and routes | |
| back to wage-labour. It does not reassure. It dissects. | |
| ## How it was built | |
| - **Base:** Qwen2.5-7B-Instruct. | |
| - **Method:** completion-style causal-LM fine-tuning, QLoRA at rank 32, adapter merged | |
| onto the fp16 base before GGUF conversion. ~37 minutes on one rented A6000-class GPU. | |
| - **Source:** six public-domain Marx/Engels works in their public-domain English | |
| translations (Moore's 1888 Manifesto, Eleanor Marx Aveling's Value Price and Profit, | |
| etc.), transcriptions from marxists.org. Roughly 1,200 completion records (authentic | |
| chunks oversampled) plus a small (~4%) modern-bridge set so the voice can reach present | |
| questions. The corpus is not published. | |
| - **Inference:** a lead-in frame ("One puts to Karl Marx this question…") elicits the | |
| first-person voice; plain chat narrates *about* Marx instead of *as* him. | |
| ## Intended use | |
| Creative writing, political-theory pedagogy in a register, tabletop and interactive | |
| fiction, voice prototyping. It is a register, not a source. Treat its output as generated | |
| prose, not as Marx's documented positions or as fact. | |
| ## Limitations and honest notes | |
| - **It invents freely** — names, dates, citations, events. It will confidently attribute a | |
| letter to a date that never existed. Read it for the voice, not the record. | |
| - **It occasionally recites.** A verbatim-regurgitation audit (24 generations vs the | |
| training corpus) found a mean longest-verbatim-run of ~7 words and one generation that | |
| reproduced a 38-word span of the Communist Manifesto. That span is Moore's 1888 | |
| translation — public domain — so it carries no copyright exposure; it is flagged here | |
| only as a transparency note about memorisation. No copyrighted translation and no | |
| synthetic bridge text was reproduced at length. | |
| - **Period framing.** It reasons from the nineteenth century outward, which is the point | |
| and also the limit. | |
| ## License | |
| `CC-BY-NC-4.0`. The source works and their English translations are public domain, so the | |
| weights could ship permissively; the non-commercial clause is a deliberately conservative | |
| choice given the synthetic modern-bridge component and the persona framing. Attribution: | |
| Ray Weiss / The Elect. Source texts: marxists.org (public domain). No warranty. | |