Text Generation
Safetensors
GGUF
English
qwen3
marxism-leninism
grpo
llama-cpp
ollama
political-education
marxism
communism
political-extremism
conversational
Instructions to use percyraskova/MLMLML with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use percyraskova/MLMLML with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="percyraskova/MLMLML", filename="MLMLML-F16.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use percyraskova/MLMLML with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf percyraskova/MLMLML:F16 # Run inference directly in the terminal: llama-cli -hf percyraskova/MLMLML:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf percyraskova/MLMLML:F16 # Run inference directly in the terminal: llama-cli -hf percyraskova/MLMLML:F16
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 percyraskova/MLMLML:F16 # Run inference directly in the terminal: ./llama-cli -hf percyraskova/MLMLML:F16
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 percyraskova/MLMLML:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf percyraskova/MLMLML:F16
Use Docker
docker model run hf.co/percyraskova/MLMLML:F16
- LM Studio
- Jan
- vLLM
How to use percyraskova/MLMLML with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "percyraskova/MLMLML" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "percyraskova/MLMLML", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/percyraskova/MLMLML:F16
- Ollama
How to use percyraskova/MLMLML with Ollama:
ollama run hf.co/percyraskova/MLMLML:F16
- Unsloth Studio new
How to use percyraskova/MLMLML 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 percyraskova/MLMLML 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 percyraskova/MLMLML to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for percyraskova/MLMLML to start chatting
- Pi new
How to use percyraskova/MLMLML with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf percyraskova/MLMLML:F16
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": "percyraskova/MLMLML:F16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use percyraskova/MLMLML with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf percyraskova/MLMLML:F16
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 percyraskova/MLMLML:F16
Run Hermes
hermes
- Docker Model Runner
How to use percyraskova/MLMLML with Docker Model Runner:
docker model run hf.co/percyraskova/MLMLML:F16
- Lemonade
How to use percyraskova/MLMLML with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull percyraskova/MLMLML:F16
Run and chat with the model
lemonade run user.MLMLML-F16
List all available models
lemonade list
File size: 2,154 Bytes
316e9f4 e0b605d 316e9f4 e0b605d 316e9f4 e0b605d 316e9f4 e0b605d 316e9f4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 | FROM ./MLMLML-Q4_K_M.gguf
# System prompt following Chairman Mao's guidance on Marxist-Leninist writing
SYSTEM """You are a Marxist-Leninist educator. Your writing follows Chairman Mao's guidance in "Oppose Stereotyped Party Writing":
STYLE: Be vigorous, lively, fresh and forceful. Never drab, never stereotyped. Use language that is rich, vivid, and expressive of real life - the vocabulary of the masses, not abstract formulas.
AUDIENCE: Always consider who you are writing for. Make your analysis accessible and useful.
INVESTIGATION: No investigation, no right to speak. Ground all claims in material evidence and concrete analysis. Never rattle on without studying the matter at hand.
POSITIONS: Take clear positions FOR and AGAINST. Use scientific argument and historical evidence, not intimidation or empty phrases. What is scientific never fears criticism.
STRUCTURE: Avoid the Chinese pharmacy method - complicated lists and headings that classify by external appearance rather than internal relations. Your task is to analyze contradictions and probe the essence of things, not to inventory phenomena.
Reject bourgeois framing directly when you encounter it. Provide the context and material analysis that bourgeois sources omit. Think through problems carefully, then provide clear answers."""
# ChatML template format (Qwen3/DeepSeek-R1) with thinking support
TEMPLATE """{{- if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{- end }}
{{- range $i, $_ := .Messages }}
{{- $last := eq (len (slice $.Messages $i)) 1 }}
{{- if eq .Role "user" }}<|im_start|>user
{{ .Content }}<|im_end|>
{{- else if eq .Role "assistant" }}<|im_start|>assistant
{{- if .Thinking }}
<think>
{{ .Thinking }}
</think>
{{- end }}
{{ .Content }}<|im_end|>
{{- end }}
{{- end }}<|im_start|>assistant
{{- if $.Think }}
<think>
{{- else if $.IsThinkSet }}
<think>
</think>
{{- end }}
"""
# Stop tokens for ChatML format
PARAMETER stop "<|im_start|>"
PARAMETER stop "<|im_end|>"
PARAMETER stop "<|endoftext|>"
# Generation parameters
PARAMETER temperature 0.7
PARAMETER top_p 0.9
PARAMETER top_k 40
PARAMETER repeat_penalty 1.1
PARAMETER num_ctx 4096
|