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Reglamento Estudiantes Universidad Del Azuay by UDA-LIDI

 »  All LLMs  »  UDA-LIDI  »  Reglamento Estudiantes Universidad Del Azuay   URL Share it on

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Model Card on HF 🤗: https://huggingface.co/UDA-LIDI/Reglamento-estudiantes-Universidad-del-Azuay 

Reglamento Estudiantes Universidad Del Azuay Benchmarks

LLME Score: 0.18533
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Reglamento Estudiantes Universidad Del Azuay (UDA-LIDI/Reglamento-estudiantes-Universidad-del-Azuay)

Reglamento Estudiantes Universidad Del Azuay Parameters and Internals

Model Type 
QA Assistant
Additional Notes 
The model acts as an assistant to answer questions about the student regulations of the University of Azuay.
Supported Languages 
es (Primary)
Training Details 
Methodology:
Fine-tuning through SFT and ORPO techniques
LLM NameReglamento Estudiantes Universidad Del Azuay
Repository 🤗https://huggingface.co/UDA-LIDI/Reglamento-estudiantes-Universidad-del-Azuay 
Merged ModelYes
Model Size8b
Required VRAM16.1 GB
Updated2025-02-22
MaintainerUDA-LIDI
Model Typellama
Instruction-BasedYes
Model Files  5.0 GB: 1-of-4   5.0 GB: 2-of-4   4.9 GB: 3-of-4   1.2 GB: 4-of-4
Supported Languageses
Model ArchitectureLlamaForCausalLM
Licensellama3
Context Length8192
Model Max Length8192
Transformers Version4.41.0.dev0
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|eot_id|>
Vocabulary Size128256
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than UDA-LIDI/Reglamento-estudiantes-Universidad-del-Azuay.

Rank the Reglamento Estudiantes Universidad Del Azuay 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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