A family of large language models optimized for on-device inference, available in 1B, 270M and 1M parameter sizes
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Welcome to Opt.Gear
This is the official Hugging Face organization for Opt.Gear, the family of On-Device language models developed by OptAI Inc. We will continuously release and update On-Device LLM, LMM and Small Agent Model designed for edge AI applications.
Build and scale yout AI services with models optimized specifically for On-Device deployment.
Opt.Gear Family of Open-Weight Models
- Opt.Gear: A family of large language models optimized for on-device inference, available in 1B and 270M parameter sizes.
- Opt.Gear-QAT: Quantization-aware large language models designed for efficient deployment on on-device platforms.
- Opt.Gear-1M: An ultra-lightweight language model designed for deployment on MCUs, including platforms such as FPGA and Raspberry Pi.
- (TBU) Opt.FGear: A tool-calling language model designed for on-device AI agents.
- (TBU) Opt.VGear: A lightweight vision-language model (VLM) for a wide range of multimodal tasks.
- (TBU) Opt.Gear-MTP: A draft model for accelerating inference in on-device environments through multi-token prediction.
models 5
OptGear/Opt.Gear-1B
Text Generation • 0.8B • Updated • 30
OptGear/Opt.Gear-1B-qat-int4-g32-unquantized
Text Generation • 0.8B • Updated • 10
OptGear/Opt.Gear-1B-qat-int4-per-channel-unquantized
Text Generation • 0.8B • Updated • 15
OptGear/Opt.Gear-1M
Text Generation • 1.04M • Updated • 27
OptGear/Opt.Gear-270M
Text Generation • 0.2B • Updated • 21
datasets 0
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