LLM EXPLORER
 LLM Explorer: A Curated Large Language Model Directory and Analytics
Dark Theme
  LLM  List    LLM Hosting    LLM Leaderboards    Blog    Newsfeed    Advertise

Qwen2.5 0.5B Instruct GPTQ Int4 by Qwen

 »  All LLMs  »  Qwen  »  Qwen2.5 0.5B Instruct GPTQ Int4   URL Share it on

  5679   
  Arxiv:2407.10671   4-bit Base model:quantized:qwen/qwen... Base model:qwen/qwen2.5-0.5b-i...   Chat   Conversational   En   Gptq   Instruct   Quantized   Qwen2   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct-GPTQ-Int4 

Qwen2.5 0.5B Instruct GPTQ Int4 Benchmarks

LLME Score: 0.28212
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2.5 0.5B Instruct GPTQ Int4 (Qwen/Qwen2.5-0.5B-Instruct-GPTQ-Int4)

Qwen2.5 0.5B Instruct GPTQ Int4 Parameters and Internals

LLM NameQwen2.5 0.5B Instruct GPTQ Int4
Repository 🤗https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct-GPTQ-Int4 
Base Model(s)  Qwen/Qwen2.5-0.5B-Instruct   Qwen/Qwen2.5-0.5B-Instruct
Model Size0.5b
Required VRAM0.5 GB
Updated2025-01-17
MaintainerQwen
Model Typeqwen2
Instruction-BasedYes
Model Files  0.5 GB
Supported Languagesen
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.39.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typefloat16
Errorsreplace

Best Alternatives to Qwen2.5 0.5B Instruct GPTQ Int4

Best Alternatives
Context / RAM
Downloads
Likes
...wen2.5 0.5B Instruct GPTQ Int832K / 0.6 GB13447
Qwen2 0.5B Instruct GPTQ Int432K / 0.7 GB66012
Qwen2 0.5B Instruct GPTQ Int832K / 1.5 GB892
Qwen2Vanilla GPTQ 8bits32K / 0.9 GB210
Qwen2Vanilla GPTQ 4bits32K / 0.7 GB200
Qwen2.5 0.5B Instruct Bnb 4bit32K / 0.5 GB170732
TinySphinx32K / 1 GB340
Acrux 500M O1 Journey32K / 1 GB2168
... Instruct Unsloth Merged 16bit32K / 1.3 GB722
... Instruct Unsloth Merged 16bit32K / 1.3 GB151
Note: green Score (e.g. "73.2") means that the model is better than Qwen/Qwen2.5-0.5B-Instruct-GPTQ-Int4.

Rank the Qwen2.5 0.5B Instruct GPTQ Int4 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  

What open-source LLMs or SLMs are you in search of? 41473 in total.

Email us: info@extractum.io. Our Privacy Policy  | Terms and Conditions  | Suggest an improvement.
Our Social Media →  
Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
  Support LLM Explorer