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---
base_model: unsloth/DeepSeek-R1-0528-Qwen3-8B
library_name: peft
pipeline_tag: text-generation
tags:
- base_model:adapter:unsloth/DeepSeek-R1-0528-Qwen3-8B
- grpo
- lora
- transformers
- trl
- unsloth
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
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#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
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## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
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#### Hardware
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#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
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## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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## Model Card Contact
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### Framework versions
- PEFT 0.18.1

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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

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---
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](https://en.prolewiki.org/).
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
```bash
# 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
```python
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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{
"alora_invocation_tokens": null,
"alpha_pattern": {},
"arrow_config": null,
"auto_mapping": {
"base_model_class": "Qwen3ForCausalLM",
"parent_library": "transformers.models.qwen3.modeling_qwen3",
"unsloth_fixed": true
},
"base_model_name_or_path": "unsloth/DeepSeek-R1-0528-Qwen3-8B",
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"target_modules": [
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],
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"task_type": "CAUSAL_LM",
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{%- if not add_generation_prompt is defined %}
{%- set add_generation_prompt = false %}
{%- endif %}
{%- set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='', is_first_sp=true, is_last_user=false) %}
{%- for message in messages %}
{%- if message['role'] == 'system' %}
{%- if ns.is_first_sp %}
{%- set ns.system_prompt = ns.system_prompt + message['content'] %}
{%- set ns.is_first_sp = false %}
{%- else %}
{%- set ns.system_prompt = ns.system_prompt + '\n\n' + message['content'] %}
{%- endif %}
{%- endif %}
{%- endfor %}
{#- Adapted from https://github.com/sgl-project/sglang/blob/main/examples/chat_template/tool_chat_template_deepseekr1.jinja #}
{%- if tools is defined and tools is not none %}
{%- set tool_ns = namespace(text='You are a helpful assistant with tool calling capabilities. ' + 'When a tool call is needed, you MUST use the following format to issue the call:\n' + '<tool▁calls▁begin><tool▁call▁begin>function<tool▁sep>FUNCTION_NAME\n' + '```json\n{"param1": "value1", "param2": "value2"}\n```<tool▁call▁end><tool▁calls▁end>\n\n' + 'Make sure the JSON is valid.' + '## Tools\n\n### Function\n\nYou have the following functions available:\n\n') %}
{%- for tool in tools %}
{%- set tool_ns.text = tool_ns.text + '\n```json\n' + (tool | tojson) + '\n```\n' %}
{%- endfor %}
{%- if ns.system_prompt|length != 0 %}
{%- set ns.system_prompt = ns.system_prompt + '\n\n' + tool_ns.text %}
{%- else %}
{%- set ns.system_prompt = tool_ns.text %}
{%- endif %}
{%- endif %}
{{- bos_token }}
{{- ns.system_prompt }}
{%- set last_index = (messages|length - 1) %}
{%- for message in messages %}
{%- set content = message['content'] %}
{%- if message['role'] == 'user' %}
{%- set ns.is_tool = false -%}
{%- set ns.is_first = false -%}
{%- set ns.is_last_user = true -%}
{%- if loop.index0 == last_index %}
{{- '<User>' + content }}
{%- else %}
{{- '<User>' + content + '<Assistant>'}}
{%- endif %}
{%- endif %}
{%- if message['role'] == 'assistant' %}
{%- if '</think>' in content %}
{%- set content = (content.split('</think>')|last) %}
{%- endif %}
{%- endif %}
{%- if message['role'] == 'assistant' and message['tool_calls'] is defined and message['tool_calls'] is not none %}
{%- set ns.is_last_user = false -%}
{%- if ns.is_tool %}
{{- '<tool▁outputs▁end>'}}
{%- endif %}
{%- set ns.is_first = false %}
{%- set ns.is_tool = false -%}
{%- set ns.is_output_first = true %}
{%- for tool in message['tool_calls'] %}
{%- set arguments = tool['function']['arguments'] %}
{%- if arguments is not string %}
{%- set arguments = arguments|tojson %}
{%- endif %}
{%- if not ns.is_first %}
{%- if content is none %}
{{- '<tool▁calls▁begin><tool▁call▁begin>' + tool['type'] + '<tool▁sep>' + tool['function']['name'] + '\n' + '```json' + '\n' + arguments + '\n' + '```' + '<tool▁call▁end>'}}
}
{%- else %}
{{- content + '<tool▁calls▁begin><tool▁call▁begin>' + tool['type'] + '<tool▁sep>' + tool['function']['name'] + '\n' + '```json' + '\n' + arguments + '\n' + '```' + '<tool▁call▁end>'}}
{%- endif %}
{%- set ns.is_first = true -%}
{%- else %}
{{- '\n' + '<tool▁call▁begin>' + tool['type'] + '<tool▁sep>' + tool['function']['name'] + '\n' + '```json' + '\n' + arguments + '\n' + '```' + '<tool▁call▁end>'}}
{%- endif %}
{%- endfor %}
{{- '<tool▁calls▁end><end▁of▁sentence>'}}
{%- endif %}
{%- if message['role'] == 'assistant' and (message['tool_calls'] is not defined or message['tool_calls'] is none) %}
{%- set ns.is_last_user = false -%}
{%- if ns.is_tool %}
{{- '<tool▁outputs▁end>' + content + '<end▁of▁sentence>'}}
{%- set ns.is_tool = false -%}
{%- else %}
{{- content + '<end▁of▁sentence>'}}
{%- endif %}
{%- endif %}
{%- if message['role'] == 'tool' %}
{%- set ns.is_last_user = false -%}
{%- set ns.is_tool = true -%}
{%- if ns.is_output_first %}
{{- '<tool▁outputs▁begin><tool▁output▁begin>' + content + '<tool▁output▁end>'}}
{%- set ns.is_output_first = false %}
{%- else %}
{{- '\n<tool▁output▁begin>' + content + '<tool▁output▁end>'}}
{%- endif %}
{%- endif %}
{%- endfor -%}
{%- if ns.is_tool %}
{{- '<tool▁outputs▁end>'}}
{%- endif %}
{#- if add_generation_prompt and not ns.is_last_user and not ns.is_tool #}
{%- if add_generation_prompt and not ns.is_tool %}
{{- '<Assistant>'}}
{%- endif %}

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{
"architectures": [
"Qwen3ForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
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"max_position_embeddings": 131072,
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"model_type": "qwen3",
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"num_hidden_layers": 36,
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"transformers_version": "4.57.3",
"unsloth_fixed": true,
"unsloth_version": "2026.1.2",
"use_cache": true,
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"vocab_size": 151936
}

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