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Instruct Yi 6B Dolly CodeAlpaca by HenryJJ

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  Autotrain compatible Dataset:databricks/databricks-... Dataset:lucasmccabe-lmi/codeal...   Endpoints compatible   Instruct   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/HenryJJ/Instruct_Yi-6B_Dolly_CodeAlpaca 

Instruct Yi 6B Dolly CodeAlpaca Benchmarks

ARC: 53.16 vs 96.7 (so35)-45%
HellaSwag: 75.3 vs 95.3 (gpt4)-21%
MMLU: 63.06 vs 88.3 (so35)-28.6%
TruthfulQA: 41.42 vs 59 (gpt4)-29.8%
WinoGrande: 75.37 vs 87.5 (gpt4)-13.9%
GSM8K: 28.35 vs 96.4 (so35)-70.6%
LLME Score: 0.17192
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Instruct Yi 6B Dolly CodeAlpaca (HenryJJ/Instruct_Yi-6B_Dolly_CodeAlpaca)
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Instruct Yi 6B Dolly CodeAlpaca Parameters and Internals

Model Type 
auto-regressive language model
Additional Notes 
Fine-tuned from Yi-6B using the Dolly15K dataset for general purposes and CodeAlpaca_20K for coding tasks. Compared with https://huggingface.co/HenryJJ/Instruct_Yi-6B_Dolly15K
Supported Languages 
English (fluent)
Training Details 
Data Sources:
databricks/databricks-dolly-15k, lucasmccabe-lmi/CodeAlpaca-20k
Methodology:
Lora fine-tuning
Context Length:
2048
Training Time:
10 hours on aws g4dn.12xlarge instance
Hardware Used:
aws g4dn.12xlarge instance
Model Architecture:
Based on Llama 2 transformer architecture
Input Output 
Input Format:
[INST]{instruction} {context}[/INST]{response}
Accepted Modalities:
text
LLM NameInstruct Yi 6B Dolly CodeAlpaca
Repository 🤗https://huggingface.co/HenryJJ/Instruct_Yi-6B_Dolly_CodeAlpaca 
Model Size6b
Required VRAM12.1 GB
Updated2025-09-15
MaintainerHenryJJ
Model Typellama
Instruction-BasedYes
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   2.2 GB: 3-of-3
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size64000
Torch Data Typefloat16

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Rank the Instruct Yi 6B Dolly CodeAlpaca 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 v20241124
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