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MagpieLM 4B SFT V0.1 by Magpie-Align

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MagpieLM 4B SFT V0.1 is an open-source language model by Magpie-Align. Features: 4b LLM, VRAM: 9GB, Context: 128K, LLM Explorer Score: 0.15.

  Arxiv:2406.08464   Axolotl Base model:finetune:nvidia/lla... Base model:nvidia/llama-3.1-mi...   Conversational Dataset:magpie-align/magpielm-...   En   Endpoints compatible   Generated from trainer   Llama   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Magpie-Align/MagpieLM-4B-SFT-v0.1 

MagpieLM 4B SFT V0.1 Benchmarks

LLME Score: 0.14953
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MagpieLM 4B SFT V0.1 (Magpie-Align/MagpieLM-4B-SFT-v0.1)
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MagpieLM 4B SFT V0.1 Parameters and Internals

Model Type 
AutoModelForCausalLM
Supported Languages 
en (unknown)
Training Details 
Data Sources:
Magpie-Align/MagpieLM-4B-SFT-v0.1
Methodology:
fine-tuning
Context Length:
8192
Hardware Used:
multi-GPU, 4 devices
LLM NameMagpieLM 4B SFT V0.1
Repository 🤗https://huggingface.co/Magpie-Align/MagpieLM-4B-SFT-v0.1 
Base Model(s)  nvidia/Llama-3.1-Minitron-4B-Width-Base   nvidia/Llama-3.1-Minitron-4B-Width-Base
Model Size4b
Required VRAM9 GB
Updated2026-05-21
MaintainerMagpie-Align
Model Typellama
Model Files  5.0 GB: 1-of-2   4.0 GB: 2-of-2   5.0 GB: 1-of-2   4.0 GB: 2-of-2   0.0 GB
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Context Length131072
Model Max Length131072
Transformers Version4.45.0.dev0
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|end_of_text|>
Vocabulary Size128256
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than Magpie-Align/MagpieLM-4B-SFT-v0.1.

Rank the MagpieLM 4B SFT V0.1 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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