metadata
license: agpl-3.0
base_model: unsloth/DeepSeek-R1-0528-Qwen3-8B
tags:
- marxism-leninism
- grpo
- llama-cpp
- ollama
- political-education
- marxism
- communism
- political-extremism
language:
- en
pipeline_tag: text-generation
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.