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MHENNcodemath by netcat420

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  Autotrain compatible   Dataset:netcat420/compsci   Endpoints compatible   Gguf   Mistral   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/netcat420/MHENNcodemath 

MHENNcodemath Benchmarks

LLME Score: 0.16026
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MHENNcodemath (netcat420/MHENNcodemath)

MHENNcodemath Parameters and Internals

Additional Notes 
Quantized model 'mhenncodemathQ4_K_M.gguf' fine-tuned for 900 steps. Tested to perform well in Rust.
Training Details 
Data Sources:
netcat420/compsci
Hardware Used:
V100 on Google Colab
LLM NameMHENNcodemath
Repository 🤗https://huggingface.co/netcat420/MHENNcodemath 
Model Size7.2b
Required VRAM28.9 GB
Updated2024-12-27
Maintainernetcat420
Model Typemistral
Model Files  4.4 GB   5.0 GB: 1-of-6   4.9 GB: 2-of-6   5.0 GB: 3-of-6   5.0 GB: 4-of-6   4.8 GB: 5-of-6   4.2 GB: 6-of-6
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureMistralForCausalLM
Licensemit
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than netcat420/MHENNcodemath.

Rank the MHENNcodemath Capabilities

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Instruction Following and Task Automation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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