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Mixtral 8x7b Instruct V0.1 Int4 Ov by OpenVINO

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  Autotrain compatible   En   Endpoints compatible   Instruct   Mixtral   Moe   Openvino   Region:us

Mixtral 8x7b Instruct V0.1 Int4 Ov Benchmarks

LLME Score: 0.20356
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 Int4 Ov Parameters and Internals

LLM NameMixtral 8x7b Instruct V0.1 Int4 Ov
Repository 🤗https://huggingface.co/OpenVINO/mixtral-8x7b-instruct-v0.1-int4-ov 
Required VRAM0 GB
Updated2024-10-07
MaintainerOpenVINO
Model Typemixtral
Instruction-BasedYes
Model Files  0.0 GB   28.7 GB   0.0 GB
Supported Languagesen
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.40.1
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typebfloat16
Mixtral 8x7b Instruct V0.1 Int4 Ov (OpenVINO/mixtral-8x7b-instruct-v0.1-int4-ov)

Best Alternatives to Mixtral 8x7b Instruct V0.1 Int4 Ov

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Context / RAM
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Likes
WizardLM 2 8x22B Beige64K / 221.4 GB183
Dolphin 2.6 Mixtral 8x7b32K / 93.6 GB4649189
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...eqlen 4096 Bs 4 Optimum 0 0 2332K /  GB540
...eqlen 4096 Bs 4 Optimum 0 0 2332K /  GB21
Empower Functions Medium32K / 93.6 GB121
Mixtral 8x7B Instruct V0.132K /  GB130
...ct V0.1 Agent Function Calling32K / 44.3 GB72
...tral 8x7B Instruct V0.1 Polish32K / 93.6 GB91
...ELT Mixtral 8x7B Instruct V0.132K / 92 GB83
Note: green Score (e.g. "73.2") means that the model is better than OpenVINO/mixtral-8x7b-instruct-v0.1-int4-ov.

Rank the Mixtral 8x7b Instruct V0.1 Int4 Ov 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072803
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