AVA Qwen1.5 7B Chat Gptq 4bit by MehdiHosseiniMoghadam

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AVA Qwen1.5 7B Chat Gptq 4bit is an open-source language model by MehdiHosseiniMoghadam. Features: 7b LLM, VRAM: 5.8GB, Context: 32K, Quantized, LLM Explorer Score: 0.13.

  4-bit   4bit   Conversational   Endpoints compatible   Gptq   Quantized   Qwen2   Region:us   Safetensors   Sharded   Tensorflow

AVA Qwen1.5 7B Chat Gptq 4bit Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

AVA Qwen1.5 7B Chat Gptq 4bit Parameters and Internals

LLM NameAVA Qwen1.5 7B Chat Gptq 4bit
Repository 🤗https://huggingface.co/MehdiHosseiniMoghadam/AVA-Qwen1.5-7B-Chat-gptq-4bit 
Model Size7b
Required VRAM5.8 GB
Updated2026-05-04
MaintainerMehdiHosseiniMoghadam
Model Typeqwen2
Model Files  4.6 GB: 1-of-2   1.2 GB: 2-of-2
GPTQ QuantizationYes
Quantization Typegptq|4bit
Model ArchitectureQwen2ForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.40.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|im_end|>
Vocabulary Size151646
Torch Data Typefloat16
Errorsreplace

Best Alternatives to AVA Qwen1.5 7B Chat Gptq 4bit

Best Alternatives
Context / RAM
Downloads
Likes
Qwen2 7B Int4 GPTQ Wikitext2128K / 5.6 GB50
CodeQwen1.5 7B Chat GPTQ Int464K / 4.9 GB150
....5 Coder 7B Instruct GPTQ Int432K / 5.6 GB41676313
Qwen2.5 7B Instruct GPTQ Int432K / 5.6 GB4507430
Qwen2.5 7B Instruct GPTQ Int832K / 8.9 GB564318
....5 Coder 7B Instruct GPTQ Int832K / 8.9 GB3324
Qwen2 7B Instruct GPTQ Int432K / 5.6 GB214328
Qwen1.5 7B Int3 GPTQ Wikitext232K / 5 GB50
Qwen2 7B Instruct GPTQ Int832K / 8.9 GB8517
Qwen1.5 7B Int4 GPTQ Wikitext232K / 5.8 GB50
Note: green Score (e.g. "73.2") means that the model is better than MehdiHosseiniMoghadam/AVA-Qwen1.5-7B-Chat-gptq-4bit.

Rank the AVA Qwen1.5 7B Chat Gptq 4bit 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 v20260328a