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Qwen2.5 1.5B Reasoning Warmup Merged by abhinav0231

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Qwen2.5 1.5B Reasoning Warmup Merged is an open-source language model by abhinav0231. Features: 1.5b LLM, VRAM: 3.1GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.32.

  4bit   Conversational   En   Endpoints compatible   Instruct   Quantized   Qwen2   Region:us   Safetensors   Unsloth
Model Card on HF 🤗: https://huggingface.co/abhinav0231/Qwen2.5-1.5B-reasoning-warmup-merged 

Qwen2.5 1.5B Reasoning Warmup Merged Benchmarks

LLME Score: 0.32115
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2.5 1.5B Reasoning Warmup Merged (abhinav0231/Qwen2.5-1.5B-reasoning-warmup-merged)
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Qwen2.5 1.5B Reasoning Warmup Merged Parameters and Internals

LLM NameQwen2.5 1.5B Reasoning Warmup Merged
Repository 🤗https://huggingface.co/abhinav0231/Qwen2.5-1.5B-reasoning-warmup-merged 
Base Model(s)  unsloth/qwen2.5-1.5b-instruct-unsloth-bnb-4bit   unsloth/qwen2.5-1.5b-instruct-unsloth-bnb-4bit
Model Size1.5b
Required VRAM3.1 GB
Updated2026-04-20
Maintainerabhinav0231
Model Typeqwen2
Instruction-BasedYes
Model Files  3.1 GB
Supported Languagesen
Quantization Type4bit
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Tokenizer ClassQwen2Tokenizer
Padding Token<|PAD_TOKEN|>
Vocabulary Size151936
Torch Data Typefloat16
Errorsreplace

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Rank the Qwen2.5 1.5B Reasoning Warmup Merged 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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