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Candle Mistral Trismegistus 7B by DanielClough

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  Autotrain compatible   Endpoints compatible   Gguf   Mistral   Q4   Quantized   Region:us   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/DanielClough/Candle_Mistral-Trismegistus-7B 

Candle Mistral Trismegistus 7B Benchmarks

ARC: 54.1 vs 96.7 (so35)-44.1%
HellaSwag: 77.91 vs 95.3 (gpt4)-18.2%
MMLU: 54.49 vs 88.3 (so35)-38.3%
TruthfulQA: 49.36 vs 59 (gpt4)-16.3%
WinoGrande: 70.17 vs 87.5 (gpt4)-19.8%
GSM8K: 9.93 vs 96.4 (so35)-89.7%
LLME Score: 0.19922
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Candle Mistral Trismegistus 7B (DanielClough/Candle_Mistral-Trismegistus-7B)

Candle Mistral Trismegistus 7B Parameters and Internals

LLM NameCandle Mistral Trismegistus 7B
Repository 🤗https://huggingface.co/DanielClough/Candle_Mistral-Trismegistus-7B 
Base Model(s)  Mistral Trismegistus 7B   teknium/Mistral-Trismegistus-7B
Model Size7b
Required VRAM14.4 GB
Updated2025-02-05
MaintainerDanielClough
Model Typemistral
Model Files  14.5 GB   2.4 GB   3.1 GB   4.1 GB   4.5 GB   4.1 GB   5.0 GB   5.4 GB   5.0 GB   5.9 GB   7.7 GB   8.2 GB   8.3 GB   9.9 GB: 1-of-2   4.5 GB: 2-of-2
GGUF QuantizationYes
Quantization Typeq4|gguf
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.34.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than DanielClough/Candle_Mistral-Trismegistus-7B.

Rank the Candle Mistral Trismegistus 7B Capabilities

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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 v20241227
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