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Nous Capybara 34B AWQ by TheBloke

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Nous Capybara 34B AWQ is an open-source language model by TheBloke. Features: 34b LLM, VRAM: 19.3GB, Context: 195K, License: mit, Quantized, LLM Explorer Score: 0.1.

  4-bit   Awq Base model:nousresearch/nous-c... Base model:quantized:nousresea... Dataset:ldjnr/lesswrong-amplif...   Dataset:ldjnr/pure-dove   Dataset:ldjnr/verified-camel   Eng   Llama   Quantized   Region:us   Safetensors   Sft   Sharded   Stablelm   Tensorflow
Model Card on HF 🤗: https://huggingface.co/TheBloke/Nous-Capybara-34B-AWQ 

Nous Capybara 34B AWQ Benchmarks

LLME Score: 0.10381
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Nous Capybara 34B AWQ (TheBloke/Nous-Capybara-34B-AWQ)
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Nous Capybara 34B AWQ Parameters and Internals

Model Type 
text generation
Additional Notes 
The first 34B Nous model with a 200K context length. Fine-tuned on the Capybara dataset with in-house data synthesis techniques.
Supported Languages 
eng (proficient)
Training Details 
Data Sources:
Nous in-house datasets, Amplify-Instruct, LessWrong
Data Volume:
20K training examples
Methodology:
fine-tuning
Context Length:
200000
Model Architecture:
Yi-34B with 200K context length
Input Output 
Input Format:
USER: {prompt} ASSISTANT:
LLM NameNous Capybara 34B AWQ
Repository 🤗https://huggingface.co/TheBloke/Nous-Capybara-34B-AWQ 
Model NameNous Capybara 34B
Model CreatorNousResearch
Base Model(s)  Nous Capybara 34B   NousResearch/Nous-Capybara-34B
Model Size34b
Required VRAM19.3 GB
Updated2026-03-29
MaintainerTheBloke
Model Typellama
Model Files  10.0 GB: 1-of-2   9.3 GB: 2-of-2
Supported Languagesen
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licensemit
Context Length200000
Model Max Length200000
Transformers Version4.35.0
Tokenizer ClassYiTokenizer
Padding Token<unk>
Vocabulary Size64000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Nous-Capybara-34B-AWQ.

Rank the Nous Capybara 34B 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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