- My Twitter Thread Question on Training Data
- Books1 and Books2 - Books1 Resources
- Bookcorpus paper
- What's in MyAI Paper, Source
- The model data is recent as of 2021.
- My Twitter Thread Question on the Model
- Language Models are Few-Shot Learners: GPT3
- Model- reinforcement learning for language models
We trained this model using Reinforcement Learning from Human Feedback (RLHF), using the same methods as InstructGPT, but with slight differences in the data collection setup.
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Azure
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K8s Source here A large machine learning job spans many nodes and runs most efficiently when it has access to all of the hardware resources on each node. This allows GPUs to cross-communicate directly using NVLink, or GPUs to directly communicate with the NIC using GPUDirect. So for many of our workloads, a single pod occupies the entire node.
We have very little HTTPS traffic, with no need for A/B testing, blue/green, or canaries. Pods communicate directly with one another on their pod IP addresses with MPI via SSH, not service endpoints. Service “discovery” is limited; we just do a one-time lookup for which pods are participating in MPI at job startup time.
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Terraform, Python, Chef, GPU workloads on 500+ node clusters






