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Qwen2 0.5B Instruct FP8 by neuralmagic

 »  All LLMs  »  neuralmagic  »  Qwen2 0.5B Instruct FP8   URL Share it on

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  Autotrain compatible   Conversational   Endpoints compatible   Fp8   Instruct   Qwen2   Region:us   Safetensors   Vllm
Model Card on HF 🤗: https://huggingface.co/neuralmagic/Qwen2-0.5B-Instruct-FP8 

Qwen2 0.5B Instruct FP8 Benchmarks

LLME Score: 0.21835
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2 0.5B Instruct FP8 (neuralmagic/Qwen2-0.5B-Instruct-FP8)

Qwen2 0.5B Instruct FP8 Parameters and Internals

Model Type 
Text
Use Cases 
Areas:
commercial, research
Primary Use Cases:
assistant-like chat
Limitations:
Use in languages other than English, Use in violation of applicable laws
Additional Notes 
Quantized using AutoFP8 with calibration samples from ultrachat.
Supported Languages 
languages_supported (English), proficiency_level ()
Training Details 
Data Sources:
ultrachat
Data Volume:
512 sequences
Methodology:
AutoFP8 quantization
Context Length:
4096
Model Architecture:
Qwen2
Input Output 
Input Format:
Text
Accepted Modalities:
Text
Output Format:
Text
Performance Tips:
Quantization reduces memory usage by 50%.
Release Notes 
Version:
1.0
Date:
2024-06-14
Notes:
Quantized weights and activations to FP8 for efficiency with vLLM.
LLM NameQwen2 0.5B Instruct FP8
Repository 🤗https://huggingface.co/neuralmagic/Qwen2-0.5B-Instruct-FP8 
Model Size0.5b
Required VRAM0.6 GB
Updated2025-02-22
Maintainerneuralmagic
Model Typeqwen2
Instruction-BasedYes
Model Files  0.6 GB
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.41.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

Quantized Models of the Qwen2 0.5B Instruct FP8

Model
Likes
Downloads
VRAM
Qwen2 0.5B Instruct 4bit1190 GB

Best Alternatives to Qwen2 0.5B Instruct FP8

Best Alternatives
Context / RAM
Downloads
Likes
Qwen2 0.5B Abyme Merge3128K / 1.3 GB620
Qwen2 0.5B Abyme Merge2128K / 0.3 GB530
Qwen2.5 0.5B Instruct32K / 1 GB1041884232
QwQ 0.5B Distilled SFT32K / 1 GB460322
Lb Reranker 0.5B V1.032K / 1 GB145063
Qwen2 0.5B Instruct32K / 1 GB204990176
Qwen2.5 Coder 0.5B Instruct32K / 1 GB4389433
FastThink 0.5B Tiny32K / 1 GB64810
Feynman Grpo Exp32K / 1 GB1897
Bellatrix Tiny 0.5B32K / 1 GB5547
Note: green Score (e.g. "73.2") means that the model is better than neuralmagic/Qwen2-0.5B-Instruct-FP8.

Rank the Qwen2 0.5B Instruct FP8 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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