Loggenix MoE 0.12B A0.08B E5 Lr5e4 B16 3060 V2 Finetuned by kshitijthakkar

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Loggenix MoE 0.12B A0.08B E5 Lr5e4 B16 3060 V2 Finetuned is an open-source language model by kshitijthakkar. Features: 133.4m LLM, VRAM: 0.3GB, Context: 1K, License: apache-2.0, MoE, Fine-Tuned, Instruction-Based, LLM Explorer Score: 0.19.

  Agentic-ai   Conversational Dataset:kshitijthakkar/loggeni...   Edge-ai   Endpoints compatible   Finetuned   From-scratch   Instruct   Instruction-following   Low-resource   Mixture-of-experts   Moe   Qwen3   Qwen3 moe   Qwen3moe   Region:us   Safetensors   Tool-use

Loggenix MoE 0.12B A0.08B E5 Lr5e4 B16 3060 V2 Finetuned Benchmarks

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

Loggenix MoE 0.12B A0.08B E5 Lr5e4 B16 3060 V2 Finetuned Parameters and Internals

LLM NameLoggenix MoE 0.12B A0.08B E5 Lr5e4 B16 3060 V2 Finetuned
Repository 🤗https://huggingface.co/kshitijthakkar/loggenix-moe-0.12B-A0.08B-e5-lr5e4-b16-3060-v2-finetuned 
Model Size133.4m
Required VRAM0.3 GB
Updated2026-05-18
Maintainerkshitijthakkar
Model Typeqwen3_moe
Instruction-BasedYes
Model Files  0.3 GB
Model ArchitectureQwen3MoeForCausalLM
Licenseapache-2.0
Context Length1024
Model Max Length1024
Transformers Version4.51.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|im_end|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

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... 0.12B A0.08B E5 Lr5e4 B4 30601K / 0.3 GB161
Note: green Score (e.g. "73.2") means that the model is better than kshitijthakkar/loggenix-moe-0.12B-A0.08B-e5-lr5e4-b16-3060-v2-finetuned.

Rank the Loggenix MoE 0.12B A0.08B E5 Lr5e4 B16 3060 V2 Finetuned 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 v20260328a