With the Intel Gaudi SynapseAI 1.13.0 release, users can run Fine Tune the Llama2 70B model using only 8 Gaudi2 Accelerators.| Intel Gaudi Developers
Bringing forth numerous enhancements and updates for an improved user experience.| Intel Gaudi Developers
One of the main challenges in training Large Language Models (LLMs) is that they are often too large to fit on a single node or even if they fit, the training may be too slow. To address this issue, their training can be parallelized across multiple Gaudi accelerators (HPUs).| Habana Developers
If you want to train a large model using Megatron-DeepSpeed, but the model you want is not included in the implementation, you can port it to the Megatron-DeepSpeed package. Assuming your model is transformer-based, you can add your implementation easily, basing it on existing code.| Habana Developers
In this release, we’ve upgraded versions of several libraries, including DeepSpeed 0.9.4, PyTorch Lightning 2.0.4 and TensorFlow 2.12.1.| Intel Gaudi Developers
Discover exceptional Gaudi2 performance on large AI models. Habana showcases breakthroughs at ISC. Explore the future of AI acceleration.| Deep Learning and AI Processor Chip Manufacturer
Streamline deep learning testing & deployment with Habana's Gaudi2 processors. Explore Equus Lab-as-a-Service for efficient AI system implementation.| Deep Learning and AI Processor Chip Manufacturer
Announcing a new End-to-End use case showing Training of a semantic segmentation model for Autonomous Driving| Intel Gaudi Developers
In the 1.9 release, we’ve upgraded versions of several libraries, including PyTorch Lightning 1.9.4, DeepSpeed 0.7.7, fairseq 0.12.3, and Horovod v0.27.0.| Intel Gaudi Developers