Una Cybertron 7B V3 OMA AWQ by TheBloke

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  4-bit   Autotrain compatible   Awq Base model:fblgit/una-cybertro... Base model:quantized:fblgit/un...   Cybertron Dataset:fblgit/tree-of-knowled...   Juanako   Mistral   Quantized   Region:us   Safetensors   Una   Xaberius

Una Cybertron 7B V3 OMA AWQ Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Una Cybertron 7B V3 OMA AWQ (TheBloke/una-cybertron-7B-v3-OMA-AWQ)
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Una Cybertron 7B V3 OMA AWQ Parameters and Internals

Model Type 
mistral
Use Cases 
Areas:
mathematics, logic, reasoning
Additional Notes 
The model can be fine-tuned via SFT and is suitable as a merge base.
Training Details 
Methodology:
UNA: Uniform Neural Alignment technique
Hardware Used:
Cybertron's H100's
LLM NameUna Cybertron 7B V3 OMA AWQ
Repository ๐Ÿค—https://huggingface.co/TheBloke/una-cybertron-7B-v3-OMA-AWQ 
Model NameUna Cybertron 7B V3 OMA
Model CreatorFBL
Base Model(s)  Una Cybertron 7B V3 OMA   fblgit/una-cybertron-7b-v3-OMA
Model Size7b
Required VRAM4.2 GB
Updated2025-09-12
MaintainerTheBloke
Model Typemistral
Model Files  4.2 GB
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/una-cybertron-7B-v3-OMA-AWQ.

Rank the Una Cybertron 7B V3 OMA 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124