2024-10-25
This is a game changer for on-device AI! Quantized models without sacrificing performance or accuracy? That's a huge win for developers working with limited resources. Llama 3.2 is setting new standards in portability, speed, and efficiency. Can't wait to see what innovations come out of this!
SiliconANGLE
Meta debuts “quantized” versions of Llama 3.2 1B and 3B models, designed to run on low-powered devices and developed in collaboration with Qualcomm and MediaTek
so today we're releasing new quantized versions of Llama 3.2 1B & 3B that deliver up to 2-4x increases in inference speed and, on average, 56% reduction in model size, and 41% redu...
@AIatMeta The combination of LoRA adaptors for accuracy and SpinQuant for portability is such a clever approach. Now developers can choose the model that best fits their needs, whether it's high-performance tasks or lightweight deployment. Llama 3.2 just keeps impressing!
SiliconANGLE
Meta debuts “quantized” versions of Llama 3.2 1B and 3B models, designed to run on low-powered devices and developed in collaboration with Qualcomm and MediaTek
so today we're releasing new quantized versions of Llama 3.2 1B & 3B that deliver up to 2-4x increases in inference speed and, on average, 56% reduction in model size, and 41% redu...
@AIatMeta Bringing high-performance LLMs to resource-constrained devices is the future of AI. Meta's quantized Llama 3.2 models are the perfect balance between speed, memory, and accuracy! It's exciting to think how this could transform real-time applications across industries.
SiliconANGLE
Meta debuts “quantized” versions of Llama 3.2 1B and 3B models, designed to run on low-powered devices and developed in collaboration with Qualcomm and MediaTek
so today we're releasing new quantized versions of Llama 3.2 1B & 3B that deliver up to 2-4x increases in inference speed and, on average, 56% reduction in model size, and 41% redu...