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NanoLM 0.3B Instruct V1 by Mxode

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  En   Instruct   Model-index   Qwen2   Region:us   Safetensors   Zh
Model Card on HF 🤗: https://huggingface.co/Mxode/NanoLM-0.3B-Instruct-v1 

NanoLM 0.3B Instruct V1 Benchmarks

MMLU Pro: 1.17
GPQA: 2.91
MUSR: 10.44
BBH: 3.1
IFEval: 15.37 vs 88 (so35)-82.5%
LLME Score: 0.23173
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
NanoLM 0.3B Instruct V1 (Mxode/NanoLM-0.3B-Instruct-v1)

NanoLM 0.3B Instruct V1 Parameters and Internals

Model Type 
text2text-generation, text-generation
Additional Notes 
The model is part of the NanoLM Collections aimed at exploring the potential of small models.
Supported Languages 
en (Fluent), zh (Fluent)
Training Details 
Methodology:
Reduced number of layers from 24 to 12
Model Architecture:
Same as Qwen/Qwen2-0.5B but reduced layers to 12
Input Output 
Accepted Modalities:
text
Performance Tips:
Configure sampling parameters appropriately for better response quality.
LLM NameNanoLM 0.3B Instruct V1
Repository 🤗https://huggingface.co/Mxode/NanoLM-0.3B-Instruct-v1 
Model Size0.3b
Required VRAM0.6 GB
Updated2025-01-14
MaintainerMxode
Model Typeqwen2
Instruction-BasedYes
Model Files  0.6 GB
Supported Languagesen zh
Model ArchitectureQwen2ForCausalLM
Licensegpl-3.0
Context Length131072
Model Max Length131072
Transformers Version4.42.4
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

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NanoLM 0.3B Instruct V1.1128K / 0.6 GB112
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Note: green Score (e.g. "73.2") means that the model is better than Mxode/NanoLM-0.3B-Instruct-v1.

Rank the NanoLM 0.3B Instruct V1 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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