-
trained a
family of
Transformers in
three ways:
pretraining on English,
finetuning on
Python pretraining on an
equal mix of
English and Python, finetuning...
- "EinsteinGPT" (for CRM) and Bloomberg's "BloombergGPT" (for finance).
Generative pretraining (GP) was a long-established
concept in
machine learning applications...
-
intermediate checkpoints after pretraining on 4.2T
tokens (not the
version at the end of
pretraining), then
pretrained further for 6T tokens, then context-extended...
- OpenAI. It
combines traditional search engine features with
generative pretrained transformers (GPT) to
generate responses,
including citations to external...
- Lipton, Zachary; Li, Mu; Smola,
Alexander J. (2024). "11.9. Large-Scale
Pretraining with Transformers". Dive into deep learning.
Cambridge New York Port...
- the
strength of this
pretraining term. This
combined objective function is
called PPO-ptx,
where "ptx"
means "Mixing
Pretraining Gradients". It was first...
- was
historically important as a
pioneer of self-supervised
generative pretraining followed by fine-tuning,
where a
large model is
trained to reproduce...
- sentences. Text-based GPT
models are
pretrained on a
large corpus of text that can be from the Internet. The
pretraining consists of
predicting the next token...
-
Contrastive Language-Image Pre-training (CLIP) is a
technique for
training a pair of
neural network models, one for
image understanding and one for text...
- Lipton, Zachary; Li, Mu; Smola,
Alexander J. (2024). "11.9. Large-Scale
Pretraining with Transformers". Dive into deep learning.
Cambridge New York Port...
