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Mixtral 8x7B Instruct V0.1 AWQ by dengpanyin

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  4-bit   Autotrain compatible   Awq   Conversational   Endpoints compatible   Instruct   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Tensorflow

Mixtral 8x7B Instruct V0.1 AWQ Benchmarks

LLME Score: 0.22185
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Mixtral 8x7B Instruct V0.1 AWQ Parameters and Internals

LLM NameMixtral 8x7B Instruct V0.1 AWQ
Repository 🤗https://huggingface.co/dengpanyin/Mixtral-8x7B-Instruct-v0.1-AWQ 
Model Size6.5b
Required VRAM24.7 GB
Updated2024-09-29
Maintainerdengpanyin
Model Typemixtral
Instruction-BasedYes
Model Files  5.0 GB: 1-of-5   5.0 GB: 2-of-5   5.0 GB: 3-of-5   5.0 GB: 4-of-5   4.7 GB: 5-of-5
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.41.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16
Mixtral 8x7B Instruct V0.1 AWQ (dengpanyin/Mixtral-8x7B-Instruct-v0.1-AWQ)

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Mixtral Instruct AWQ32K / 24.7 GB8439942
Mixtral 8x7B Instruct V0.1 AWQ32K / 24.7 GB2048415
Mixtral 8x7B Instruct V0.1 AWQ32K / 24.7 GB538757
Dolphin 2.7 Mixtral 8x7b AWQ32K / 24.7 GB292520
...0.1 LimaRP ZLoss DARE TIES AWQ32K / 24.7 GB3973
...xtral Instruct AWQ Clone Dec2332K / 24.7 GB70
...ixtral Instruct 8x7b Zloss AWQ32K / 24.7 GB642
...utLM Mixtral 8x7B Instruct AWQ32K / 24.7 GB1302
...Instruct V0.1 LimaRP ZLoss AWQ32K / 24.7 GB101
Dolphin 2.6 Mixtral 8x7b AWQ32K / 24.7 GB1213
Note: green Score (e.g. "73.2") means that the model is better than dengpanyin/Mixtral-8x7B-Instruct-v0.1-AWQ.

Rank the Mixtral 8x7B Instruct V0.1 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 v2024072803
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