MLMLML - Machine Learning Marxist-Leninist Models of Language

A GRPO fine-tuned language model for Marxist-Leninist political education and analysis.

Model Description

This model is fine-tuned from unsloth/DeepSeek-R1-0528-Qwen3-8B using Group Relative Policy Optimization (GRPO) on a curated dataset of Marxist-Leninist Q&A pairs from ProleWiki.

The training rewards:

  • Ideological firmness: Clear positions grounded in material analysis
  • Coherence: Self-consistent, well-structured responses
  • Accuracy: Faithful to Marxist-Leninist theory and historical evidence

The training penalizes:

  • "Both-sidesing" and false balance
  • Hedging and evasive language
  • Bourgeois framing and ahistorical claims

Writing Style

Following Chairman Mao's guidance in "Oppose Stereotyped Party Writing":

  • Vigorous, lively, fresh and forceful - never drab or stereotyped
  • Audience-aware - "When shooting an arrow, one must aim at the target"
  • Investigation-based - "No investigation, no right to speak"
  • Clear positions - FOR and AGAINST, using scientific argument

Usage

Download and Convert to GGUF

# Clone the repo
git lfs install
git clone https://huggingface.co/percyraskova/MLMLML
cd MLMLML

# Convert to GGUF (requires llama.cpp)
python ~/llama.cpp/convert_hf_to_gguf.py . --outfile MLMLML-F16.gguf --outtype f16

# Quantize to Q4_K_M
~/llama.cpp/build/bin/llama-quantize MLMLML-F16.gguf MLMLML-Q4_K_M.gguf Q4_K_M

# Create Ollama model
ollama create mlmlml -f Modelfile
ollama run mlmlml

Direct with Transformers

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("percyraskova/MLMLML")
tokenizer = AutoTokenizer.from_pretrained("percyraskova/MLMLML")

inputs = tokenizer("What is imperialism?", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0]))

Training Details

  • Base model: unsloth/DeepSeek-R1-0528-Qwen3-8B
  • Method: GRPO (Group Relative Policy Optimization)
  • Dataset: ProleWiki Q&A pairs (~4500 samples)
  • Epochs: 2
  • Hardware: NVIDIA A100 80GB

Limitations

This model is designed for educational purposes about Marxist-Leninist theory and analysis. It takes clear ideological positions and is not intended to be "neutral" on class struggle, imperialism, or other questions where Marxism-Leninism has definite answers.

License

Apache 2.0

Citation

If you use this model, please cite ProleWiki as the source of training data.

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