-
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...
- "EinsteinGPT" (for CRM) and Bloomberg's "BloombergGPT" (for finance).
Generative pretraining (GP) was a long-established
concept in
machine learning applications...
-
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...
- was
historically important as a
pioneer of self-supervised
generative pretraining followed by fine-tuning,
where a
large model is
trained to reproduce...
-
detect the
presence of data in a
pretraining dataset. It
presents a
sentence suspected to be
present in the
pretraining dataset, and
computes the log-likelihood...
- OpenAI. It
combines traditional search engine features with
generative pretrained transformers (GPT) to
generate responses,
including citations to external...
-
trained a
family of
Transformers in
three ways:
pretraining on English,
finetuning on
Python pretraining on an
equal mix of
English and Python, finetuning...
- Lipton, Zachary; Li, Mu; Smola,
Alexander J. (2024). "11.9. Large-Scale
Pretraining with Transformers". Dive into deep learning.
Cambridge New York Port...
- is
typically an
unlabeled large corpus, such as The Pile.
Tasks for
pretraining and fine-tuning
commonly include:
language modeling next-sentence prediction...
-
wells contain water.
Pretraining on this day ends when the rats
locate and
consume water from all 5
baited wells.
Following pretraining, rats are
given 8...
