LLM EXPLORER
 LLM Explorer: A Curated Large Language Model Directory and Analytics
Dark Theme
  LLM  List    LLM Hosting    LLM Leaderboards    Blog    Newsfeed    Advertise

MoE 3x7b QA Code Inst by nextai-team

 »  All LLMs  »  nextai-team  »  MoE 3x7b QA Code Inst   URL Share it on

  4   
  Autotrain compatible   Code   Conversational   En   Endpoints compatible   Mistral   Mixtral   Moe   Qa   Reasoning   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/nextai-team/Moe-3x7b-QA-Code-Inst 

MoE 3x7b QA Code Inst Benchmarks

ARC: 64.25 vs 96.7 (so35)-33.6%
HellaSwag: 84.6 vs 95.3 (gpt4)-11.2%
MMLU: 62.15 vs 88.3 (so35)-29.6%
TruthfulQA: 63.15 vs 59 (gpt4)7%
WinoGrande: 77.43 vs 87.5 (gpt4)-11.5%
GSM8K: 48.6 vs 96.4 (so35)-49.6%
LLME Score: 0.14646
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MoE 3x7b QA Code Inst (nextai-team/Moe-3x7b-QA-Code-Inst)
🌟 Advertise your project 🚀

MoE 3x7b QA Code Inst Parameters and Internals

Model Type 
Question Answering, Code Generation
Use Cases 
Applications:
Automated coding assistance, Technical support bots, Educational tools for programming, Enhancing code review processes
Limitations:
Model may exhibit biases from training data, Performance varies based on query specificity and context
Supported Languages 
en (high)
Training Details 
Data Sources:
technical documentation, open-source code repositories, Stack Overflow questions and answers, programming-related texts
Model Architecture:
Mixture of Experts (MoE)
Responsible Ai Considerations 
Fairness:
The model may exhibit biases from its training data.
Transparency:
Not explicitly mentioned.
Accountability:
Users are encouraged to critically assess model outputs.
Mitigation Strategies:
Employ the model responsibly to avoid generating harmful or unsafe code.
LLM NameMoE 3x7b QA Code Inst
Repository 🤗https://huggingface.co/nextai-team/Moe-3x7b-QA-Code-Inst 
Model Size18.5b
Required VRAM37 GB
Updated2025-11-11
Maintainernextai-team
Model Typemixtral
Model Files  4.9 GB: 1-of-8   4.9 GB: 2-of-8   4.9 GB: 3-of-8   5.0 GB: 4-of-8   4.9 GB: 5-of-8   4.9 GB: 6-of-8   5.0 GB: 7-of-8   2.5 GB: 8-of-8
Supported Languagesen
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

Best Alternatives to MoE 3x7b QA Code Inst

Best Alternatives
Context / RAM
Downloads
Likes
Topxtral 4x7B V0.132K / 37.1 GB97294
EastAsia 4x7B MoE Experiment32K / 37.1 GB4871
Lumina 3.532K / 37.1 GB12070
Hyperion 3.0 Mixtral 3x7B32K / 37.1 GB44
Blitz AI MoE V0.732K / 37.1 GB81
Blitz AI MoE V0.432K / 37.1 GB61
HeroBophades 3x7B32K / 37.1 GB73
Wizard Kun Lake 3x7B MoE32K / 37.1 GB21
Pearl 3x7B32K / 37.1 GB62
NaruMOE 3x7B V232K / 37.1 GB90
Note: green Score (e.g. "73.2") means that the model is better than nextai-team/Moe-3x7b-QA-Code-Inst.

Rank the MoE 3x7b QA Code Inst Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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  

What open-source LLMs or SLMs are you in search of? 51557 in total.

Email us: info@extractum.io. Our Privacy Policy  | Terms and Conditions  | Suggest an improvement.
Our Social Media →  
Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
  Support LLM Explorer