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Philosophy Mistral by Heralax

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  Autotrain compatible Base model:heralax/philosophy-... Base model:quantized:heralax/p...   Conversational   Endpoints compatible   Generated from trainer   Ggml   Gguf   Mistral   Pytorch   Q8   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/Heralax/philosophy-mistral 

Philosophy Mistral Benchmarks

LLME Score: 0.18031
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Philosophy Mistral (Heralax/philosophy-mistral)
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Philosophy Mistral Parameters and Internals

Additional Notes 
This model has been trained on a narrow domain, focusing on philosophical texts from the Gutenberg project. It's very knowledgeable in this area due to memorization and uses a new dataset setting which may make it less detailed but more concise in responses. Known limitations include lack of generalist instruct data, limiting it primarily to QA.
Training Details 
Data Sources:
The Problems of Philosophy (Bertrand Russell), Beyond Good and Evil (Nietzsche), Thus Spake Zarathustra: A Book for All and None (Nietzsche), The Prince (Machiavelli), Second Treatise of Government
Methodology:
training on top 5 books on Gutenberg, new dataset setting lacking generalist instruct data
Hardware Used:
multi-GPU with 6 devices
LLM NamePhilosophy Mistral
Repository 🤗https://huggingface.co/Heralax/philosophy-mistral 
Base Model(s)  Heralax/philosophy-llm-mistral-pretrain   Heralax/philosophy-llm-mistral-pretrain
Model Size7.2b
Required VRAM7.7 GB
Updated2025-09-23
MaintainerHeralax
Model Typemistral
Model Files  14.5 GB   7.7 GB   14.5 GB
GGML QuantizationYes
GGUF QuantizationYes
Quantization Typeggml|q8|gguf
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.45.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token<|end_of_text|>
Vocabulary Size32001
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than Heralax/philosophy-mistral.

Rank the Philosophy Mistral Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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
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