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Chirp 01 by ozone-research

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Chirp 01 is an open-source language model by ozone-research. Features: 3b LLM, VRAM: 6.2GB, Context: 32K, License: other, Instruction-Based, LLM Explorer Score: 0.26.

Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-3b-ins...   Instruct   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/ozone-research/Chirp-01 

Chirp 01 Benchmarks

MMLU Pro: 27.87
GPQA: 2.91
MUSR: 15.56
BBH: 25.04
IFEval: 63.48 vs 88 (so35)-27.9%
MATH Lvl 5: 34.67
LLME Score: 0.26106
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Chirp 01 (ozone-research/Chirp-01)
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Chirp 01 Parameters and Internals

LLM NameChirp 01
Repository 🤗https://huggingface.co/ozone-research/Chirp-01 
Base Model(s)  Qwen/Qwen2.5-3B-Instruct   Qwen/Qwen2.5-3B-Instruct
Model Size3b
Required VRAM6.2 GB
Updated2026-03-29
Maintainerozone-research
Model Typeqwen2
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   1.2 GB: 2-of-2
Model ArchitectureQwen2ForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.49.0.dev0
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typefloat16
Errorsreplace

Best Alternatives to Chirp 01

Best Alternatives
Context / RAM
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Likes
Saba2 3B128K / 6.2 GB240
Tessa T1 3B117K / 6.2 GB165
UIGEN T1.5 3B117K / 6.2 GB111
Qwen2.5 3B Instruct32K / 6.2 GB10226936444
SmallThinker 3B Preview32K / 6.8 GB30529412
FlameDesigner Qwen2.5 3B V132K / 6.2 GB2330
Qwen2.5 Coder 3B Instruct32K / 6.2 GB451109101
Qwen2.5 3B Instruct Heretic32K / 6.2 GB921
Menda 3B 50032K / 6.2 GB150
Menda 3B 75032K / 6.2 GB231
Note: green Score (e.g. "73.2") means that the model is better than ozone-research/Chirp-01.

Rank the Chirp 01 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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