yuq-zhou/2026-05-o-b0p3-a0p5-gc0p75-exp-td8p0-tw10p0-mbz-bridge-q3-1p7b
TEXT GENERATIONPricing:Input $0.32 / Cached $0.064 / Output $1.6Concurrent Unit Cost:1Model Size:2BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 15, 2026Architecture:Transformer Featherless Exclusive Cold
The yuq-zhou/2026-05-o-b0p3-a0p5-gc0p75-exp-td8p0-tw10p0-mbz-bridge-q3-1p7b is a 1.7 billion parameter causal language model, developed by yuq-zhou. This model is provided as a research artifact backup in standard HuggingFace format. Its primary purpose is for research and experimental use, offering a compact model size for exploration.
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Model Overview
The yuq-zhou/2026-05-o-b0p3-a0p5-gc0p75-exp-td8p0-tw10p0-mbz-bridge-q3-1p7b is a 1.7 billion parameter causal language model. It is presented as a research artifact backup, available in the standard HuggingFace format, making it compatible with AutoModelForCausalLM.from_pretrained for easy integration into existing workflows.
Key Characteristics
- Parameter Count: 1.7 billion parameters, offering a relatively compact size for experimental and research purposes.
- Format: Provided as a standard HuggingFace checkpoint, ensuring broad compatibility and ease of use within the HuggingFace ecosystem.
- Nature: Designated as a research artifact backup, indicating its origin from experimental work.
Potential Use Cases
This model is suitable for:
- Research and Development: Ideal for researchers and developers exploring causal language models at a smaller scale.
- Experimental Prototyping: Can be used for rapid prototyping and testing of language model applications where a larger model might be overkill.
- Resource-Constrained Environments: Its smaller size may make it suitable for environments with limited computational resources, though specific performance characteristics would need evaluation.