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OpenHermes 2.5 Strix Philosophy Mistral 7B LoRA by sayhan

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OpenHermes 2.5 Strix Philosophy Mistral 7B LoRA is an open-source language model by sayhan. Features: 7b LLM, VRAM: 14.4GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.13.

Base model:quantized:teknium/o... Base model:teknium/openhermes-...   Conversational Dataset:sayhan/strix-philosoph...   En   Endpoints compatible   Gguf   Lora   Mistral   Quantized   Region:us   Safetensors   Sharded   Tensorflow   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/sayhan/OpenHermes-2.5-Strix-Philosophy-Mistral-7B-LoRA 

OpenHermes 2.5 Strix Philosophy Mistral 7B LoRA Benchmarks

LLME Score: 0.12881
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
OpenHermes 2.5 Strix Philosophy Mistral 7B LoRA (sayhan/OpenHermes-2.5-Strix-Philosophy-Mistral-7B-LoRA)
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OpenHermes 2.5 Strix Philosophy Mistral 7B LoRA Parameters and Internals

Model Type 
trl, text-generation-inference, unsloth, mistral, gguf
Additional Notes 
LoRA rank: 8, LoRA alpha: 16, LoRA dropout: 0, Rank-stabilized LoRA: Yes, Number of epochs: 3, Learning rate: 1e-5, Batch size: 2, Gradient accumulation steps: 4, Weight decay: 0.01
Supported Languages 
en (English)
Training Details 
Data Sources:
sayhan/strix-philosophy-qa
Methodology:
LoRA (Low-Rank Adaptation)
LLM NameOpenHermes 2.5 Strix Philosophy Mistral 7B LoRA
Repository 🤗https://huggingface.co/sayhan/OpenHermes-2.5-Strix-Philosophy-Mistral-7B-LoRA 
Base Model(s)  teknium/OpenHermes-2.5-Mistral-7B   teknium/OpenHermes-2.5-Mistral-7B
Model Size7b
Required VRAM14.4 GB
Updated2026-03-24
Maintainersayhan
Model Files  0.1 GB   4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3   3.8 GB   14.5 GB   2.7 GB   3.5 GB   3.2 GB   4.1 GB   4.4 GB   4.1 GB   5.0 GB   5.1 GB   5.0 GB   5.9 GB   7.7 GB   14.5 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureAutoModelForCausalLM
Licenseapache-2.0
Model Max Length32768
Is Biasednone
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesk_proj|v_proj|down_proj|o_proj|q_proj|up_proj|gate_proj
LoRA Alpha16
LoRA Dropout0
R Param8

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Note: green Score (e.g. "73.2") means that the model is better than sayhan/OpenHermes-2.5-Strix-Philosophy-Mistral-7B-LoRA.

Rank the OpenHermes 2.5 Strix Philosophy Mistral 7B LoRA 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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