AV BI Qwen2.5 14B PT BR Instruct by amadeusai

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AV BI Qwen2.5 14B PT BR Instruct is an open-source language model by amadeusai. Features: 14b LLM, VRAM: 29.7GB, Context: 128K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.17.

  Autotrain compatible Base model:finetune:qwen/qwen2...   Base model:qwen/qwen2.5-14b   Chat   Conversational   Endpoints compatible   Instruct   Pt   Qwen2   Region:us   Safetensors   Sharded   Tensorflow

AV BI Qwen2.5 14B PT BR Instruct Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
AV BI Qwen2.5 14B PT BR Instruct (amadeusai/AV-BI-Qwen2.5-14B-PT-BR-Instruct)
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AV BI Qwen2.5 14B PT BR Instruct Parameters and Internals

LLM NameAV BI Qwen2.5 14B PT BR Instruct
Repository ๐Ÿค—https://huggingface.co/amadeusai/AV-BI-Qwen2.5-14B-PT-BR-Instruct 
Base Model(s)  Qwen/Qwen2.5-14B   Qwen/Qwen2.5-14B
Model Size14b
Required VRAM29.7 GB
Updated2025-05-20
Maintaineramadeusai
Model Typeqwen2
Instruction-BasedYes
Model Files  5.0 GB: 1-of-6   5.0 GB: 2-of-6   5.0 GB: 3-of-6   5.0 GB: 4-of-6   5.0 GB: 5-of-6   4.7 GB: 6-of-6   0.0 GB
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length131072
Model Max Length131072
Transformers Version4.46.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

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...14B Instruct 1M GRPO Reasoning986K / 29.7 GB394
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Note: green Score (e.g. "73.2") means that the model is better than amadeusai/AV-BI-Qwen2.5-14B-PT-BR-Instruct.

Rank the AV BI Qwen2.5 14B PT BR Instruct Capabilities

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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  
Multi-Language Support and Translation  

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Release v20260327b