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Tuesday, 28 June 2022

DALL·E 2 pre-training mitigations

OpenAI 4 years ago 25

OpenAI implemented content policy guardrails into DALL·E 2's training process to mitigate risks before making the image generation model widely available. The company applied pre-training mitigations but did not specify measurable benchmarks or quantified risk reductions in this announcement. The guardrails aim to prevent the model from generating images that violate OpenAI's content policy when users interact with the deployed system.

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Content Moderation Image Generation

Announcing Evaluation on the Hub

Hugging Face 4 years ago 43

Hugging Face launched Evaluation on the Hub, a no-code tool powered by AutoTrain that allows users to evaluate any machine learning model on any dataset directly through the platform. The tool was used to evaluate hundreds of models on key datasets, with results automatically added to model cards in a standardized format. This enables researchers and practitioners to compare model performance, reproduce results, and select models for deployment without writing code or worrying about implementation inconsistencies.

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Hugging Face Model Evaluation

Accelerate Large Model Training using DeepSpeed

Hugging Face 4 years ago 16

The Accelerate library enables training of large models using DeepSpeed's ZeRO optimization technique, which distributes optimizer states, gradients, and model parameters across GPUs and CPU memory. In a benchmark with a 900M-parameter DeBERTa model, DeepSpeed ZeRO Stage-2 achieved a batch size of 40 compared to DDP's maximum of 8, resulting in 3.5X faster training time without performance loss. This allows users to fit larger models and batch sizes on existing hardware without modifying their training code.

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Model Training

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