Description
📌 Source: gpt-image2.art · Creator: gpt-image2.art
Real People
InstructGPT RLHF Architecture Diagram
✦ Prompt
Clean technical diagram explaining the InstructGPT training process via RLHF (Reinforcement Learning from Human Feedback). Three-stage pipeline shown left to right with arrows. Stage 1 'Supervised Fine-Tuning (SFT)': pretrained GPT model + human-written demonstration data → fine-tuned SFT model. Stage 2 'Reward Model Training': SFT model generates multiple outputs → human labelers rank them → train Reward Model (RM). Stage 3 'PPO Reinforcement Learning': SFT model interacts with prompts → RM scores outputs → PPO algorithm updates the policy → final InstructGPT model. Use boxed model icons (rounded rectangles with model name labels), arrows with stage transitions, small data icons for input/output. Soft pastel color coding by stage (blue, green, orange). Style: research paper figure, minimal, axis-grid background, English labels.
| Model | Unknown |
|---|---|
| Language | English |
| Source | gpt-image2.art |
| Creator | gpt-image2.art |
| Collected | August 8, 2026 |
Try the prompts using this demo:
Clean technical diagram explaining the InstructGPT training process via RLHF (Reinforcement Learning from Human Feedback). Three-stage pipeline shown left to right with arrows. Stage 1 'Supervised Fine-Tuning (SFT)': pretrained GPT model + human-written demonstration data → fine-tuned SFT model. Stage 2 'Reward Model Training': SFT model generates multiple outputs → human labelers rank them → train Reward Model (RM). Stage 3 'PPO Reinforcement Learning': SFT model interacts with prompts → RM scores outputs → PPO algorithm updates the policy → final InstructGPT model. Use boxed model icons (rounded rectangles with model name labels), arrows with stage transitions, small data icons for input/output. Soft pastel color coding by stage (blue, green, orange). Style: research paper figure, minimal, axis-grid background, English labels.
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