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suzhou3.2
tripplet-research/suzhou3.2
suzhou3.2 is a text generation model from tripplet-research. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
A 12 billion parameter instruction-tuned language model by Triplet Research. Suzhou 3.2 is a weighted merge of Suzhou 3.1 and Qwen2.5-3B, designed to improve reasoning and math capabilities.
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9B
17.9 GB on disk
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.safetensors17.9 GB · 100%
At a glance
- Task
- Text Generation
- Library
- transformers
- License
- apache-2.0
- Access
- Public
- Created
- Apr 26, 2026
- Updated
- Apr 26, 2026
- SHA
- e0b9559e
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Base models
Model card
From the Hugging Face model README
Suzhou 3.2
A 12 billion parameter instruction-tuned language model by Triplet Research. Suzhou 3.2 is a weighted merge of Suzhou 3.1 and Qwen2.5-3B, designed to improve reasoning and math capabilities.
Merge Details
- Method: Weighted blending (70% Suzhou 3.1 + 30% Qwen2.5-3B)
- Model A: Suzhou 3.1 - strong agent/tool-use, reasoning
- Model B: Qwen2.5-3B-Instruct - math reasoning, general knowledge
- Target: 12B parameters
Key Features
- 12B parameters
- 262K context window
- Strong reasoning and chain-of-thought capabilities
- Tool calling and agent support
- Multilingual support (29+ languages)
- Mixed attention architecture (linear + full attention layers)
Architecture
- Type: Causal Language Model
- Architecture: Qwen3.5 Text
- Layers: 32
- Parameters: 12B
Safetensors
- 12B parameters
Quickstart
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("Triplet-Research/suzhou-3.2")
tokenizer = AutoTokenizer.from_pretrained("Triplet-Research/suzhou-3.2")
- Task
- Text Generation
- Library
- transformers
- License
- apache-2.0
- Languages
- en, zh, ko, ja, fr, es
- Created
- Apr 26, 2026
- Updated
- Apr 26, 2026