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Wukong Phi 3 Instruct Ablated by RESMPDEV

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  Autotrain compatible   Conversational   Custom code Dataset:cognitivecomputations/...   En   Endpoints compatible   Instruct   Phi3   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/RESMPDEV/Wukong-Phi-3-Instruct-Ablated 

Wukong Phi 3 Instruct Ablated Benchmarks

LLME Score: 0.18875
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Wukong Phi 3 Instruct Ablated (RESMPDEV/Wukong-Phi-3-Instruct-Ablated)

Wukong Phi 3 Instruct Ablated Parameters and Internals

Model Type 
chat, text-generation
Supported Languages 
en (proficient)
Training Details 
Data Sources:
cognitivecomputations/Dolphin-2.9
Methodology:
dealigned chat fine-tuning
LLM NameWukong Phi 3 Instruct Ablated
Repository 🤗https://huggingface.co/RESMPDEV/Wukong-Phi-3-Instruct-Ablated 
Model Size3.8b
Required VRAM7.7 GB
Updated2025-02-22
MaintainerRESMPDEV
Model Typephi3
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   2.7 GB: 2-of-2
Supported Languagesen
Model ArchitecturePhi3ForCausalLM
Licensemit
Context Length4096
Model Max Length4096
Transformers Version4.40.2
Tokenizer ClassLlamaTokenizer
Padding Token<|endoftext|>
Vocabulary Size32064
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than RESMPDEV/Wukong-Phi-3-Instruct-Ablated.

Rank the Wukong Phi 3 Instruct Ablated 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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