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ANIMA Phi Neptune Mistral 7B AWQ by TheBloke

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Model Card on HF 🤗: https://huggingface.co/TheBloke/ANIMA-Phi-Neptune-Mistral-7B-AWQ 

ANIMA Phi Neptune Mistral 7B AWQ Benchmarks

LLME Score: 0.11343
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 AWQ (TheBloke/ANIMA-Phi-Neptune-Mistral-7B-AWQ)
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ANIMA Phi Neptune Mistral 7B AWQ Parameters and Internals

Model Type 
mistral
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
Training Time:
1 Epoch x 5hrs on 1 x T4 Small, 1 Epoch x 1hr on 1 x A100, 1 Epoch x 15mins on 1 x A100
Hardware Used:
1 x T4 Small, 1 x A100, 1 x A100
LLM NameANIMA Phi Neptune Mistral 7B AWQ
Repository 🤗https://huggingface.co/TheBloke/ANIMA-Phi-Neptune-Mistral-7B-AWQ 
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
AWQ QuantizationYes
Quantization Typeawq
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-AWQ.

Rank the ANIMA Phi Neptune Mistral 7B AWQ 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 v20241124
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