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FusionNet 34Bx2 MoE AWQ by TheBloke

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  4-bit   Autotrain compatible   Awq Base model:quantized:tomgrc/fu... Base model:tomgrc/fusionnet 34...   Conversational   En   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/TheBloke/FusionNet_34Bx2_MoE-AWQ 

FusionNet 34Bx2 MoE AWQ Benchmarks

LLME Score: 0.1626
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
FusionNet 34Bx2 MoE AWQ (TheBloke/FusionNet_34Bx2_MoE-AWQ)

FusionNet 34Bx2 MoE AWQ Parameters and Internals

Model Type 
mixtral
Use Cases 
Areas:
text generation
Additional Notes 
This model is tuned for MoE method which boosts performance significantly. For AutoAWQ inference, AutoAWQ 0.1.8 or later versions should be installed for compatibility.
Supported Languages 
en (fine-tuned)
Training Details 
Data Sources:
VMware Open Instruct
Methodology:
fine-tuned using MoE method
Context Length:
8192
Model Architecture:
FusionNet with 60.8B parameters, utilizing MoE (Mixture of Experts) method
Input Output 
Input Format:
[INST] <> {system_message} <> {prompt} [/INST]
Accepted Modalities:
text
Output Format:
text generation
LLM NameFusionNet 34Bx2 MoE AWQ
Repository 🤗https://huggingface.co/TheBloke/FusionNet_34Bx2_MoE-AWQ 
Model NameFusionNet 34Bx2 MoE
Model CreatorSuqin Zhang
Base Model(s)  FusionNet 34Bx2 MoE   TomGrc/FusionNet_34Bx2_MoE
Model Size8.9b
Required VRAM32.8 GB
Updated2025-02-05
MaintainerTheBloke
Model Typemixtral
Model Files  9.9 GB: 1-of-4   9.9 GB: 2-of-4   9.9 GB: 3-of-4   3.1 GB: 4-of-4
Supported Languagesen
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMixtralForCausalLM
Licensemit
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token<s>
Vocabulary Size64000
Torch Data Typefloat16

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Rank the FusionNet 34Bx2 MoE 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 v20241227
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