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Piaget 0.6B by gustavecortal

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Piaget 0.6B is an open-source language model by gustavecortal. Features: 0.6b LLM, VRAM: 1.2GB, Context: 40K, License: mit, LLM Explorer Score: 0.19.

Base model:finetune:qwen/qwen3...   Base model:qwen/qwen3-0.6b   Conversational Dataset:cognitivecomputations/... Dataset:generalreasoning/gener... Dataset:gustavecortal/psycholo...   Emotion   En   Philosophy   Psychology   Qwen3   Reasoning   Region:us   Safetensors   Social
Model Card on HF 🤗: https://huggingface.co/gustavecortal/Piaget-0.6B 

Piaget 0.6B Benchmarks

LLME Score: 0.19262
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Piaget 0.6B (gustavecortal/Piaget-0.6B)
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Piaget 0.6B Parameters and Internals

LLM NamePiaget 0.6B
Repository 🤗https://huggingface.co/gustavecortal/Piaget-0.6B 
Base Model(s)  Qwen/Qwen3-0.6B   Qwen/Qwen3-0.6B
Model Size0.6b
Required VRAM1.2 GB
Updated2026-06-12
Maintainergustavecortal
Model Typeqwen3
Model Files  1.2 GB
Supported Languagesen
Model ArchitectureQwen3ForCausalLM
Licensemit
Context Length40960
Model Max Length40960
Transformers Version4.53.0
Tokenizer ClassQwen2Tokenizer
Padding Token<|im_end|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to Piaget 0.6B

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Context / RAM
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Qwen3 Reranker 0.6B40K / 1.2 GB2150586368
Qwen3 0.6B FP840K / 1.1 GB207990362
Privasis Cleaner 0.6B40K / 1.2 GB35210
Qwen 0.6B ConvFill40K / 1.2 GB1160
GLM 5.1 Qwen3 0.6B CoNDeNse40K / 1.5 GB4452
Qwen3 0.6B40K / 1.2 GB19717220
Palindrome Sft Qwen340K / 2.4 GB1410
Foggen40K / 1.2 GB355
Palindrome Sft V2 Qwen340K / 2.4 GB810
Qwen3 0.6B Cybertown SFT40K / 1.2 GB160
Note: green Score (e.g. "73.2") means that the model is better than gustavecortal/Piaget-0.6B.

Rank the Piaget 0.6B 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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