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Marx 3B by acrastt

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Marx 3B is an open-source language model by acrastt. Features: 3b LLM, VRAM: 6.8GB, Context: 2K, License: apache-2.0, HF Score: 41.7, LLM Explorer Score: 0.14, Arc: 43.2, HellaSwag: 72.7, MMLU: 28.5, TruthfulQA: 39.1, WinoGrande: 65.6, GSM8K: 1.3.

  Autotrain compatible Dataset:totally-not-an-llm/eve...   En   Endpoints compatible   Llama   Model-index   Pytorch   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/acrastt/Marx-3B 

Marx 3B Benchmarks

ARC: 43.17 vs 96.7 (so35)-55.4%
HellaSwag: 72.68 vs 95.3 (gpt4)-23.7%
MMLU: 28.46 vs 88.3 (so35)-67.8%
TruthfulQA: 39.09 vs 59 (gpt4)-33.7%
WinoGrande: 65.59 vs 87.5 (gpt4)-25%
GSM8K: 1.29 vs 96.4 (so35)-98.7%
LLME Score: 0.14259
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Marx 3B (acrastt/Marx-3B)
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Marx 3B Parameters and Internals

Model Type 
text-generation
Additional Notes 
This model was an initial experiment in finetuning, so performance may vary significantly from expectations. Available in GGML and GPTQ quantizations for different deployment environments.
Training Details 
Data Sources:
EverythingLM Data(ShareGPT format more cleaned)
Data Volume:
unknown
Methodology:
finetuning
Training Time:
1 epoch
Input Output 
Input Format:
{prompt}
Output Format:
text
Performance Tips:
Don't expect high performance as it was a finetuning experiment
LLM NameMarx 3B
Repository 🤗https://huggingface.co/acrastt/Marx-3B 
Model Size3b
Required VRAM6.8 GB
Updated2025-09-23
Maintaineracrastt
Model Typellama
Model Files  6.8 GB   6.8 GB
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.30.2
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than acrastt/Marx-3B.

Rank the Marx 3B Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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