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New16b3e by Daemontatox

 »  All LLMs  »  Daemontatox  »  New16b3e   URL Share it on

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  4bit   Autotrain compatible Base model:finetune:unsloth/qw... Base model:unsloth/qwen2-0.5b-...   Conversational   En   Endpoints compatible   Instruct   Pytorch   Quantized   Qwen2   Region:us   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/Daemontatox/new16b3e 

New16b3e Benchmarks

LLME Score: 0.1977
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
New16b3e (Daemontatox/new16b3e)

New16b3e Parameters and Internals

Model Type 
text-generation-inference, transformers
Additional Notes 
Model was trained 2x faster with Unsloth and Huggingface's TRL library.
LLM NameNew16b3e
Repository 🤗https://huggingface.co/Daemontatox/new16b3e 
Base Model(s)  unsloth/Qwen2-0.5B-Instruct-bnb-4bit   unsloth/Qwen2-0.5B-Instruct-bnb-4bit
Model Size0.5b
Required VRAM1 GB
Updated2024-12-03
MaintainerDaemontatox
Model Typeqwen2
Instruction-BasedYes
Model Files  1.0 GB
Supported Languagesen
Quantization Type4bit
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.41.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typefloat16
Errorsreplace

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Qwen2 0.5B Instruct Bnb 4bit32K / 0.5 GB63804
Note: green Score (e.g. "73.2") means that the model is better than Daemontatox/new16b3e.

Rank the New16b3e 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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