Explore the diverse landscape of AI/ML frameworks, including, PyTorch, JAX, and Keras. This video breaks down what these frameworks are, how they differ, and when to choose one over another for model training, inference, and fine tuning. We cover additional specific purpose frameworks like Nvidia’s Triton Inference Server and Hugging Face’s TGI and PEFT, providing insights into their strengths for building and deploying efficient AI models.
Chapters:
0:00 – Introduction to AI/ML frameworks
0:34 – Defining your models: The builders
0:57 – Keras: The user friendly API
1:30 – PyTorch and JAX: Granular control and performance
2:23 – Inference: putting models to work
3:38 – vLLM for LLM serving
4:13 – Fine tuning: The learning process
4:58 – Conclusion and recap
Resources:
Keras Overview → https://goo.gle/3JOiCCX
PyTorch Overview → https://goo.gle/3LyarLE
Get Started with JAX → https://goo.gle/3LUjlTK
Get Started with vLLM → https://goo.gle/47xuYbQ
Hugging Face PEFT Documentation → https://goo.gle/49MZyzz
NVIDIA Triton Inference Server → https://goo.gle/4qTBv8f
Subscribe to Google Cloud Tech → https://goo.gle/GoogleCloudTech
#GoogleCloud #AIFrameworks
Speakers: Duncan Campbell
Products Mentioned: AI Infrastructure, JAX, PyTorch, Keras, Cloud TPUs
