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Fast Apply V0.2 Qwen2.5 Coder 7B Ft by quocdat25

 »  All LLMs  »  quocdat25  »  Fast Apply V0.2 Qwen2.5 Coder 7B Ft   URL Share it on

  88   
  Arxiv:1910.09700   4bit   Autotrain compatible   Codegen   Endpoints compatible   Quantized   Qwen2   Region:us   Safetensors   Sharded   Tensorflow   Unsloth

Fast Apply V0.2 Qwen2.5 Coder 7B Ft Benchmarks

LLME Score: 0.26203
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Fast Apply V0.2 Qwen2.5 Coder 7B Ft Parameters and Internals

LLM NameFast Apply V0.2 Qwen2.5 Coder 7B Ft
Repository 🤗https://huggingface.co/quocdat25/fast-apply-v0.2-qwen2.5-Coder-7B-ft 
Model Size7b
Required VRAM15.2 GB
Updated2024-10-16
Maintainerquocdat25
Model Typeqwen2
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
Quantization Type4bit
Generates CodeYes
Model ArchitectureQwen2ForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.44.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|PAD_TOKEN|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace
Fast Apply V0.2 Qwen2.5 Coder 7B Ft (quocdat25/fast-apply-v0.2-qwen2.5-Coder-7B-ft)

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Note: green Score (e.g. "73.2") means that the model is better than quocdat25/fast-apply-v0.2-qwen2.5-Coder-7B-ft.

Rank the Fast Apply V0.2 Qwen2.5 Coder 7B Ft 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 v2024072803
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