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IcaroLM by alexsobolev

 »  All LLMs  »  alexsobolev  »  IcaroLM   URL Share it on

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  4bit   Autotrain compatible   Conversational   Endpoints compatible   Gguf   Quantized   Qwen2   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/alexsobolev/IcaroLM 

IcaroLM Benchmarks

LLME Score: 0.16103
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
IcaroLM (alexsobolev/IcaroLM)
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IcaroLM Parameters and Internals

Model Type 
Language Model
Use Cases 
Applications:
Mobile chatbots and virtual assistants, Emotional support applications, Task automation on mobile devices
LLM NameIcaroLM
Repository 🤗https://huggingface.co/alexsobolev/IcaroLM 
Model Size1.5b
Required VRAM3.1 GB
Updated2025-09-23
Maintaineralexsobolev
Model Typeqwen2
Model Files  3.1 GB
Quantization Type4bit
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length131072
Model Max Length131072
Transformers Version4.41.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|PAD_TOKEN|>
Vocabulary Size151936
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than alexsobolev/IcaroLM.

Rank the IcaroLM 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 v20241124
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