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GML Mistral Merged V1 by mlabonne

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GML Mistral Merged V1 is an open-source language model by mlabonne. Features: 9b LLM, VRAM: 18GB, Context: 32K, License: apache-2.0, Merged, LLM Explorer Score: 0.14, Arc: 43.8, HellaSwag: 57.9, MMLU: 64.1.

  Merged Model   Endpoints compatible   Mistral   Model-index   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/mlabonne/GML-Mistral-merged-v1 

GML Mistral Merged V1 Benchmarks

ARC: 43.77 vs 96.7 (so35)-54.7%
HellaSwag: 57.89 vs 95.3 (gpt4)-39.3%
MMLU: 64.13 vs 88.3 (so35)-27.4%
LLME Score: 0.14117
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
GML Mistral Merged V1 (mlabonne/GML-Mistral-merged-v1)
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GML Mistral Merged V1 Parameters and Internals

Model Type 
text-generation
Additional Notes 
This model is a merge of the following models made with mergekit: [quantumaikr/quantum-v0.01](https://huggingface.co/quantumaikr/quantum-v0.01), [mncai/mistral-7b-dpo-v5](https://huggingface.co/mncai/mistral-7b-dpo-v5) with the configuration using slice sources from both models and a passthrough merge method in bfloat16 dtype.
LLM NameGML Mistral Merged V1
Repository 🤗https://huggingface.co/mlabonne/GML-Mistral-merged-v1 
Merged ModelYes
Model Size9b
Required VRAM18 GB
Updated2026-05-19
Maintainermlabonne
Model Typemistral
Model Files  9.9 GB: 1-of-2   8.1 GB: 2-of-2
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typebfloat16

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...raAI Foredoomed 9B EXL 2.8 Bpw32K / 3.7 GB50
Note: green Score (e.g. "73.2") means that the model is better than mlabonne/GML-Mistral-merged-v1.

Rank the GML Mistral Merged V1 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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