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Qwen2.5 1.5B Instruct AWQ by Qwen

 »  All LLMs  »  Qwen  »  Qwen2.5 1.5B Instruct AWQ   URL Share it on

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  Arxiv:2407.10671   4-bit   Autotrain compatible   Awq Base model:quantized:qwen/qwen... Base model:qwen/qwen2.5-1.5b-i...   Chat   Conversational   En   Endpoints compatible   Instruct   Quantized   Qwen2   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct-AWQ 

Qwen2.5 1.5B Instruct AWQ Benchmarks

LLME Score: 0.26582
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 Instruct AWQ (Qwen/Qwen2.5-1.5B-Instruct-AWQ)

Qwen2.5 1.5B Instruct AWQ Parameters and Internals

Model Type 
Causal Language Models
Additional Notes 
Supports long-context input up to 128K tokens and can generate output up to 8K tokens. Multilingual support for over 29 languages.
Supported Languages 
languages_supported (en), proficiency_level (English and Multilingual Support)
Training Details 
Methodology:
Pretraining & Post-training
Context Length:
32768
Model Architecture:
transformers with RoPE, SwiGLU, RMSNorm, Attention QKV bias and tied word embeddings
Input Output 
Input Format:
apply_chat_template
Accepted Modalities:
text
Output Format:
text
LLM NameQwen2.5 1.5B Instruct AWQ
Repository 🤗https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct-AWQ 
Base Model(s)  Qwen/Qwen2.5-1.5B-Instruct   Qwen/Qwen2.5-1.5B-Instruct
Model Size1.5b
Required VRAM1.6 GB
Updated2025-02-05
MaintainerQwen
Model Typeqwen2
Instruction-BasedYes
Model Files  1.6 GB
Supported Languagesen
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.41.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typefloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than Qwen/Qwen2.5-1.5B-Instruct-AWQ.

Rank the Qwen2.5 1.5B Instruct AWQ 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 v20241227
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