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Llama3.1 8B Instruct CoT by xinchen9

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Model Card on HF 🤗: https://huggingface.co/xinchen9/Llama3.1_8B_Instruct_CoT 

Llama3.1 8B Instruct CoT Benchmarks

MMLU Pro: 20.88
GPQA: 6.94
MUSR: 13.17
BBH: 21.14
IFEval: 29.74 vs 88 (so35)-66.2%
MATH Lvl 5: 5.29
LLME Score: 0.26306
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama3.1 8B Instruct CoT (xinchen9/Llama3.1_8B_Instruct_CoT)

Llama3.1 8B Instruct CoT Parameters and Internals

Model Type 
text-generation
Additional Notes 
The model was fine-tuned on a dataset from the CoT_Collection, with the training step set to 30,000 and utilizing a batch size of 8 per device across 5 GPUs. The learning rate employed was 0.0003.
Training Details 
Data Sources:
CoT_Collection
Methodology:
Fine-tuning with 30,000 training steps
Hardware Used:
5 GPUs
LLM NameLlama3.1 8B Instruct CoT
Repository 🤗https://huggingface.co/xinchen9/Llama3.1_8B_Instruct_CoT 
Model Size8b
Required VRAM16.1 GB
Updated2025-02-05
Maintainerxinchen9
Model Typellama
Instruction-BasedYes
Model Files  5.0 GB: 1-of-4   5.0 GB: 2-of-4   4.9 GB: 3-of-4   1.2 GB: 4-of-4
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length131072
Model Max Length131072
Transformers Version4.44.0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than xinchen9/Llama3.1_8B_Instruct_CoT.

Rank the Llama3.1 8B Instruct CoT 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 v20241227
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