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OpenOrca Stx AWQ by TheBloke

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  4-bit   Autotrain compatible   Awq Base model:lightblue/openorca ... Base model:quantized:lightblue...   Dataset:csebuetnlp/xlsum   Dataset:khalidalt/tydiqa-goldp Dataset:snow simplified japane...   Ja   Llama   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/TheBloke/OpenOrca_Stx-AWQ 

OpenOrca Stx AWQ Benchmarks

LLME Score: 0.11187
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
OpenOrca Stx AWQ (TheBloke/OpenOrca_Stx-AWQ)
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OpenOrca Stx AWQ Parameters and Internals

Model Type 
llama
Use Cases 
Primary Use Cases:
Closed Question Answering in Japanese
Supported Languages 
ja (Highly proficient)
Training Details 
Data Sources:
snow_simplified_japanese_corpus, khalidalt/tydiqa-goldp, csebuetnlp/xlsum
Data Volume:
13,167 samples
Methodology:
QLoRA finetuning
Context Length:
4096
Input Output 
Input Format:
{prompt}
Accepted Modalities:
text
LLM NameOpenOrca Stx AWQ
Repository 🤗https://huggingface.co/TheBloke/OpenOrca_Stx-AWQ 
Model NameOpenOrca Stx
Model CreatorLightblue Technology Inc.
Base Model(s)  Openorca Stx   lightblue/openorca_stx
Model Size2b
Required VRAM7.2 GB
Updated2025-08-21
MaintainerTheBloke
Model Typellama
Model Files  7.2 GB
Supported Languagesja
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.33.1
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32002
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/OpenOrca_Stx-AWQ.

Rank the OpenOrca Stx 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  
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Release v20241124
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