Distilabeled Marcoro14 7B Slerp Full by argilla

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Distilabeled Marcoro14 7B Slerp Full Benchmarks

Distilabeled Marcoro14 7B Slerp Full (argilla/distilabeled-Marcoro14-7B-slerp-full)
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Distilabeled Marcoro14 7B Slerp Full Parameters and Internals

Model Type 
text-generation
Additional Notes 
The model achieves high benchmark scores, demonstrating improvements in text generation tasks due to its fine-tuning process.
Training Details 
Data Sources:
argilla/distilabel-intel-orca-dpo-pairs
Methodology:
DPO fine-tune with a filter on datasets (removing ties and chosen_score >= 8)
Training Time:
less than 2 hours
Hardware Used:
1 x A100 80GB in runpod
Release Notes 
Notes:
The model is fine-tuned on the argilla/distilabel-intel-orca-dpo-pairs dataset using a filtered version to improve data quality.
LLM NameDistilabeled Marcoro14 7B Slerp Full
Repository ๐Ÿค—https://huggingface.co/argilla/distilabeled-Marcoro14-7B-slerp-full 
Model Size7b
Required VRAM14.4 GB
Updated2025-09-16
Maintainerargilla
Model Typemistral
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Supported Languagesen
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 argilla/distilabeled-Marcoro14-7B-slerp-full.

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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  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124