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Cerebrum RP by ChavyvAkvar

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  Autotrain compatible Base model:aetherresearch/cere... Base model:finetune:aetherrese...   Conversational   Dataset:xilabs/pippa-alpaca   En   Endpoints compatible   Mistral   Model-index   Region:us   Safetensors   Sft   Sharded   Tensorflow   Trl   Unsloth

Cerebrum RP Benchmarks

ARC: 59.3 vs 96.7 (so35)-38.7%
HellaSwag: 82.89 vs 95.3 (gpt4)-13%
MMLU: 62.5 vs 88.3 (so35)-29.2%
TruthfulQA: 42.97 vs 59 (gpt4)-27.2%
WinoGrande: 78.69 vs 87.5 (gpt4)-10.1%
GSM8K: 38.89 vs 96.4 (so35)-59.7%
LLME Score: 0.21493
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Cerebrum RP Parameters and Internals

LLM NameCerebrum RP
Repository 🤗https://huggingface.co/ChavyvAkvar/Cerebrum-RP 
Base Model(s)  AetherResearch/Cerebrum-1.0-7b   AetherResearch/Cerebrum-1.0-7b
Model Size7b
Required VRAM14.4 GB
Updated2024-10-18
MaintainerChavyvAkvar
Model Typemistral
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Supported Languagesen
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.38.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typefloat16
Cerebrum RP (ChavyvAkvar/Cerebrum-RP)

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Note: green Score (e.g. "73.2") means that the model is better than ChavyvAkvar/Cerebrum-RP.

Rank the Cerebrum RP 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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Release v2024072803
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