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ABEJA Qwen2.5 7B Japanese V0.1 by abeja

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ABEJA Qwen2.5 7B Japanese V0.1 is an open-source language model by abeja. Features: 7b LLM, VRAM: 15.2GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.2.

Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-7b-ins...   Conversational   Endpoints compatible   Instruct   Ja   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/abeja/ABEJA-Qwen2.5-7b-Japanese-v0.1 

ABEJA Qwen2.5 7B Japanese V0.1 Benchmarks

LLME Score: 0.19987
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
ABEJA Qwen2.5 7B Japanese V0.1 (abeja/ABEJA-Qwen2.5-7b-Japanese-v0.1)
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ABEJA Qwen2.5 7B Japanese V0.1 Parameters and Internals

LLM NameABEJA Qwen2.5 7B Japanese V0.1
Repository 🤗https://huggingface.co/abeja/ABEJA-Qwen2.5-7b-Japanese-v0.1 
Base Model(s)  Qwen/Qwen2.5-7B-Instruct   Qwen/Qwen2.5-7B-Instruct
Model Size7b
Required VRAM15.2 GB
Updated2026-02-26
Maintainerabeja
Model Typeqwen2
Instruction-BasedYes
Model Files  4.9 GB: 1-of-4   4.9 GB: 2-of-4   4.3 GB: 3-of-4   1.1 GB: 4-of-4
Supported Languagesja
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.46.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to ABEJA Qwen2.5 7B Japanese V0.1

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Likes
Qwen2.5 7B Instruct 1M986K / 15.4 GB58209362
Hush Qwen2.5 7B RP V1.4 1M986K / 15.2 GB42
Qwen2.5 7B RRP 1M986K / 15.2 GB206
Qwen2.5 7B CelestialHarmony 1M986K / 14.8 GB37
Q2.5 Instruct 1M Harmony986K / 15.2 GB42
Impish QWEN 7B 1M986K / 15.2 GB215
COCO 7B Instruct 1M986K / 15.2 GB34
Apollo 7B986K / 15.2 GB60
Graph R1 7B986K / 15.3 GB53
Qwen2.5 7B Sky R1 Mini986K / 15.2 GB70
Note: green Score (e.g. "73.2") means that the model is better than abeja/ABEJA-Qwen2.5-7b-Japanese-v0.1.

Rank the ABEJA Qwen2.5 7B Japanese V0.1 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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