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NeuralBeagle 11B by vicgalle

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NeuralBeagle 11B is an open-source language model by vicgalle. Features: 11b LLM, VRAM: 21.4GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.12, Arc: 73.3, HellaSwag: 87.6, MMLU: 63.8, GSM8K: 59.

  11b Base model:finetune:vicgalle/f... Base model:vicgalle/franken-be...   Conversational Dataset:argilla/distilabel-int...   Dpo   Endpoints compatible   Merge   Mistral   Model-index   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/vicgalle/NeuralBeagle-11B 

NeuralBeagle 11B Benchmarks

ARC: 73.29 vs 96.7 (so35)-24.2%
HellaSwag: 87.61 vs 95.3 (gpt4)-8.1%
MMLU: 63.8 vs 88.3 (so35)-27.7%
GSM8K: 58.98 vs 96.4 (so35)-38.8%
LLME Score: 0.12133
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
NeuralBeagle 11B (vicgalle/NeuralBeagle-11B)
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NeuralBeagle 11B Parameters and Internals

Model Type 
text-generation
Additional Notes 
DPO'd from vicgalle/franken-Beagle-11B, a Beagle-like model upscaled to 11B. It is a frankenmerge model created using mergekit. Then, we applied DPO over a high-quality preference dataset.
LLM NameNeuralBeagle 11B
Repository 🤗https://huggingface.co/vicgalle/NeuralBeagle-11B 
Base Model(s)  Franken Beagle 11B   vicgalle/franken-Beagle-11B
Model Size11b
Required VRAM21.4 GB
Updated2026-05-08
Maintainervicgalle
Model Typemistral
Model Files  4.9 GB: 1-of-5   5.0 GB: 2-of-5   4.9 GB: 3-of-5   4.9 GB: 4-of-5   1.7 GB: 5-of-5
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than vicgalle/NeuralBeagle-11B.

Rank the NeuralBeagle 11B 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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