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Qwen2 7B Reuploaded by rombodawg

 »  All LLMs  »  rombodawg  »  Qwen2 7B Reuploaded   URL Share it on

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  Autotrain compatible   Conversational   En   Endpoints compatible   Pretrained   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/rombodawg/qwen2-7b-reuploaded 

Qwen2 7B Reuploaded Benchmarks

LLME Score: 0.19953
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2 7B Reuploaded (rombodawg/qwen2-7b-reuploaded)

Qwen2 7B Reuploaded Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
research, commercial applications
Primary Use Cases:
Language understanding, language generation, multilingual capability, coding, mathematics, reasoning
Supported Languages 
English (proficient), Chinese (proficient), Multilingual (varied proficiency)
Training Details 
Methodology:
Transformer architecture with SwiGLU activation, attention QKV bias, group query attention.
Model Architecture:
Transformer
Input Output 
Accepted Modalities:
text
Performance Tips:
It is suggested to not use base language models for text generation directly. Instead, apply post-training techniques like SFT, RLHF, continued pretraining on this model.
LLM NameQwen2 7B Reuploaded
Repository 🤗https://huggingface.co/rombodawg/qwen2-7b-reuploaded 
Model Size7b
Required VRAM15.4 GB
Updated2025-02-22
Maintainerrombodawg
Model Typeqwen2
Model Files  4.0 GB: 1-of-4   3.9 GB: 2-of-4   3.9 GB: 3-of-4   3.6 GB: 4-of-4
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length131072
Model Max Length131072
Transformers Version4.37.2
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 rombodawg/qwen2-7b-reuploaded.

Rank the Qwen2 7B Reuploaded 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  

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