
A Quick Guide to Quantization for LLMs
No se pudo agregar al carrito
Add to Cart failed.
Error al Agregar a Lista de Deseos.
Error al eliminar de la lista de deseos.
Error al añadir a tu biblioteca
Error al seguir el podcast
Error al dejar de seguir el podcast
-
Narrado por:
-
De:
This story was originally published on HackerNoon at: https://hackernoon.com/a-quick-guide-to-quantization-for-llms.
Quantization is a technique that reduces the precision of a model’s weights and activations.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #ai, #llm, #large-language-models, #artificial-intelligence, #quantization, #technology, #quantization-for-llms, #ai-quantization-explained, and more.
This story was written by: @jmstdy95. Learn more about this writer by checking @jmstdy95's about page, and for more stories, please visit hackernoon.com.
Quantization is a technique that reduces the precision of a model’s weights and activations. Quantization helps by: Shrinking model size (less disk storage) Reducing memory usage (fits in smaller GPUs/CPUs) Cutting down compute requirements.