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QCammel 13 AWQ by TheBloke

 »  All LLMs  »  TheBloke  »  QCammel 13 AWQ   URL Share it on

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  Arxiv:2302.13971   Arxiv:2305.12031   Arxiv:2305.14314   4-bit   Autotrain compatible   Awq   Base model:augtoma/qcammel-13 Base model:quantized:augtoma/q...   En   Llama   Llama2   Pytorch   Qcammel-13   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/TheBloke/qCammel-13-AWQ 

QCammel 13 AWQ Benchmarks

LLME Score: 0.1069
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
QCammel 13 AWQ (TheBloke/qCammel-13-AWQ)
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QCammel 13 AWQ Parameters and Internals

Model Type 
llama
Training Details 
Data Volume:
Distilled dataset of 15,000 instructions
Methodology:
QLoRA
Model Architecture:
Llama 2 architecture, an auto-regressive language model using a decoder only transformer architecture.
Input Output 
Input Format:
Text input
Accepted Modalities:
text
Output Format:
Text output
LLM NameQCammel 13 AWQ
Repository 🤗https://huggingface.co/TheBloke/qCammel-13-AWQ 
Model NameqCammel 13
Model Creatoraugtoma
Base Model(s)  QCammel 13   augtoma/qCammel-13
Model Size2b
Required VRAM7.2 GB
Updated2025-10-01
MaintainerTheBloke
Model Typellama
Model Files  7.2 GB
Supported Languagesen
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length4096
Model Max Length4096
Transformers Version4.32.0.dev0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/qCammel-13-AWQ.

Rank the QCammel 13 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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