ChatGPT is a sibling model to InstructGPT, which is trained to follow an instruction in a prompt and provide a detailed response.
- 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 and does offline inference :
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.
- My Twitter Thread Question on the Model
- Language Models are Few-Shot Learners: GPT3
- Model- reinforcement learning for language models
- Illutstrating Reinforcement Learning from Human Feedback Tutorial
- InstructGPT Blog Post
- InstructGPT Model Card
- Models Referred to as GPT 3.5
- OpenAI comes clean about GPT 3.5
- Possibly davinci-003
- Azure
- 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.
- Code completion
- Semantic search
