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Jessi V0.1 Qwen2.5 7B Instruct by neopolita

 »  All LLMs  »  neopolita  »  Jessi V0.1 Qwen2.5 7B Instruct   URL Share it on

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Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-7b-ins...   Instruct   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/neopolita/jessi-v0.1-qwen2.5-7b-instruct 

Jessi V0.1 Qwen2.5 7B Instruct Benchmarks

MMLU Pro: 36.29
GPQA: 5.37
MUSR: 7.34
BBH: 35.09
IFEval: 72.75 vs 88 (so35)-17.3%
LLME Score: 0.33726
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Jessi V0.1 Qwen2.5 7B Instruct (neopolita/jessi-v0.1-qwen2.5-7b-instruct)

Jessi V0.1 Qwen2.5 7B Instruct Parameters and Internals

LLM NameJessi V0.1 Qwen2.5 7B Instruct
Repository 🤗https://huggingface.co/neopolita/jessi-v0.1-qwen2.5-7b-instruct 
Base Model(s)  Qwen/Qwen2.5-7B-Instruct   Qwen/Qwen2.5-7B-Instruct
Model Size7b
Required VRAM15.2 GB
Updated2025-01-21
Maintainerneopolita
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
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.47.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than neopolita/jessi-v0.1-qwen2.5-7b-instruct.

Rank the Jessi V0.1 Qwen2.5 7B Instruct 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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