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Qwenwared by Daemontatox

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  4bit   Autotrain compatible   Conversational   En   Endpoints compatible   Instruct   Pytorch   Quantized   Qwen2   Region:us   Sharded   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/Daemontatox/qwenwared 

Qwenwared Benchmarks

LLME Score: 0.2085
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwenwared (Daemontatox/qwenwared)

Qwenwared Parameters and Internals

LLM NameQwenwared
Repository 🤗https://huggingface.co/Daemontatox/qwenwared 
Base Model(s)  unsloth/qwen2-7b-instruct-bnb-4bit   unsloth/qwen2-7b-instruct-bnb-4bit
Model Size7b
Required VRAM15.2 GB
Updated2024-08-11
MaintainerDaemontatox
Model Typeqwen2
Instruction-BasedYes
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 Length32768
Model Max Length32768
Transformers Version4.41.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typefloat16
Errorsreplace

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Qwen2.5 7B Instruct V1.232K / 15.2 GB4030
Note: green Score (e.g. "73.2") means that the model is better than Daemontatox/qwenwared.

Rank the Qwenwared 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  

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Release v20241217
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