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Qwen2 7B Matter 0.1 Slim A by munish0838

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  4bit   Autotrain compatible   Conversational   En   Endpoints compatible   Pytorch   Quantized   Qwen2   Region:us   Sft   Sharded   Trl   Unsloth

Qwen2 7B Matter 0.1 Slim A Benchmarks

LLME Score: 0.22269
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Qwen2 7B Matter 0.1 Slim A Parameters and Internals

LLM NameQwen2 7B Matter 0.1 Slim A
Repository 🤗https://huggingface.co/munish0838/Qwen2-7b-Matter-0.1-Slim-A 
Base Model(s)  unsloth/Qwen2-7b-bnb-4bit   unsloth/Qwen2-7b-bnb-4bit
Model Size7b
Required VRAM15.2 GB
Updated2024-10-18
Maintainermunish0838
Model Typeqwen2
Model Files  4.9 GB: 1-of-4   4.9 GB: 2-of-4   4.3 GB: 3-of-4   1.1 GB: 4-of-4
Supported Languagesen
Quantization Type4bit
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length131072
Model Max Length131072
Transformers Version4.41.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|PAD_TOKEN|>
Vocabulary Size152064
Torch Data Typefloat16
Qwen2 7B Matter 0.1 Slim A (munish0838/Qwen2-7b-Matter-0.1-Slim-A)

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Note: green Score (e.g. "73.2") means that the model is better than munish0838/Qwen2-7b-Matter-0.1-Slim-A.

Rank the Qwen2 7B Matter 0.1 Slim A 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 v2024072803
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