ANIMA Phi Neptune Mistral 7B GPTQ by TheBloke

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ANIMA Phi Neptune Mistral 7B GPTQ Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
ANIMA Phi Neptune Mistral 7B GPTQ (TheBloke/ANIMA-Phi-Neptune-Mistral-7B-GPTQ)
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ANIMA Phi Neptune Mistral 7B GPTQ Parameters and Internals

Model Type 
mistral
Additional Notes 
The model is specialized in biomimicry and environmental science applications, integrating aspects of various scientific disciplines.
Training Details 
Data Sources:
Severian/Biomimicry, emrgnt-cmplxty/sciphi-textbooks-are-all-you-need, fmars/wiki_stem, fblgit/tree-of-knowledge, Severian/Bio-Design-Process
Data Volume:
730k data points total
Methodology:
Combined fine-tuning across multiple datasets
Input Output 
Input Format:
[INST] {prompt} [/INST]
LLM NameANIMA Phi Neptune Mistral 7B GPTQ
Repository ๐Ÿค—https://huggingface.co/TheBloke/ANIMA-Phi-Neptune-Mistral-7B-GPTQ 
Model NameAnima Phi Neptune Mistral 7B
Model CreatorSeverian
Base Model(s)  ANIMA Phi Neptune Mistral 7B   Severian/ANIMA-Phi-Neptune-Mistral-7B
Model Size7b
Required VRAM4.2 GB
Updated2025-09-23
MaintainerTheBloke
Model Typemistral
Model Files  4.2 GB
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureMistralForCausalLM
Licensemit
Context Length32768
Model Max Length32768
Transformers Version4.34.0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/ANIMA-Phi-Neptune-Mistral-7B-GPTQ.

Rank the ANIMA Phi Neptune Mistral 7B GPTQ 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 v20241124