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Damysus Coder V0.1 by prince-canuma

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  4bit   Autotrain compatible Base model:finetune:unsloth/mi... Base model:unsloth/mistral-7b-...   Codegen   Conversational   En   Endpoints compatible   Instruct   Mistral   Pytorch   Quantized   Region:us   Safetensors   Sharded   Tensorflow   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/prince-canuma/Damysus-Coder-v0.1 

Damysus Coder V0.1 Benchmarks

ARC: 60.92 vs 96.7 (so35)-37%
HellaSwag: 84.01 vs 95.3 (gpt4)-11.8%
MMLU: 60.54 vs 88.3 (so35)-31.4%
TruthfulQA: 64.2 vs 59 (gpt4)8.8%
WinoGrande: 77.11 vs 87.5 (gpt4)-11.9%
GSM8K: 39.27 vs 96.4 (so35)-59.3%
LLME Score: 0.16112
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Damysus Coder V0.1 (prince-canuma/Damysus-Coder-v0.1)
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Damysus Coder V0.1 Parameters and Internals

Model Type 
text-generation-inference, transformers, unsloth, mistral, trl
Additional Notes 
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
LLM NameDamysus Coder V0.1
Repository 🤗https://huggingface.co/prince-canuma/Damysus-Coder-v0.1 
Base Model(s)  unsloth/mistral-7b-instruct-v0.2-bnb-4bit   unsloth/mistral-7b-instruct-v0.2-bnb-4bit
Model Size7b
Required VRAM14.4 GB
Updated2025-09-23
Maintainerprince-canuma
Model Typemistral
Instruction-BasedYes
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3   4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Supported Languagesen
Quantization Type4bit
Generates CodeYes
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.38.2
Tokenizer ClassLlamaTokenizer
Padding 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 prince-canuma/Damysus-Coder-v0.1.

Rank the Damysus Coder V0.1 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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