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NanoLM 0.3B Instruct V2 by Mxode

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Model Card on HF 🤗: https://huggingface.co/Mxode/NanoLM-0.3B-Instruct-v2 

NanoLM 0.3B Instruct V2 Benchmarks

MMLU Pro: 1.49
GPQA: 1.45
MUSR: 7.57
BBH: 2.21
IFEval: 16.68 vs 88 (so35)-81%
LLME Score: 0.23315
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 V2 (Mxode/NanoLM-0.3B-Instruct-v2)

NanoLM 0.3B Instruct V2 Parameters and Internals

Model Type 
text2text-generation
Supported Languages 
en (English)
Training Details 
Context Length:
4000
Model Architecture:
Qwen2ForCausalLM
LLM NameNanoLM 0.3B Instruct V2
Repository 🤗https://huggingface.co/Mxode/NanoLM-0.3B-Instruct-v2 
Model Size0.3b
Required VRAM0.6 GB
Updated2025-01-17
MaintainerMxode
Model Typeqwen2
Instruction-BasedYes
Model Files  0.6 GB
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Licensegpl-3.0
Context Length131072
Model Max Length131072
Transformers Version4.42.0
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to NanoLM 0.3B Instruct V2

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NanoLM 0.3B Instruct V1.1128K / 0.6 GB112
NanoLM 0.3B Instruct V1128K / 0.6 GB50
Note: green Score (e.g. "73.2") means that the model is better than Mxode/NanoLM-0.3B-Instruct-v2.

Rank the NanoLM 0.3B Instruct V2 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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Release v20241227
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