-
Here is a simple rundown what ChatGPT had to say about it:
Combining `argparse` and `Hydra` is a useful approach when you want to manage configurations using Hydra while still maintaining some fl…
-
@cocktailpeanut as evoked in another thread
--optimizer_args "relative_step=False" "scale_parameter=False" "warmup_init=False"
--lr_scheduler constant_with_warmup
**THIS SETTING IS ABSOLUTE C…
-
Support Vector Machines (SVM) is a supervised machine learning algorithm for classification and regression tasks. SVM works by finding the optimal hyperplane that separates data points of different cl…
-
Original Repository: https://github.com/ml-explore/mlx-examples/
Listing out examples from there which would be nice to have. We don't expect the models to work out the moment they are translated to …
-
Dear repository owner,
I am reaching out to express our admiration for your repository.
I am the author who recently published a paper titled "Learning Semantic Proxies from Visual Prompts for P…
-
Parameter-efficient transfer learning for NLP
May I ask why you opt not to implement the "adapter" from this paper? Is it due to performance or anything else?
-
Thanks for your impressive work! I'm curious about the training time required for the Unpaired Day2Night model on the BDD100K.
It took me around 1 day on a single A100 GPU for only 1k steps. This …
-
The current model relies on trial and error iterations to calibrate the model, is there a more efficient way to improve efficiency
-
### Description
Scikit offers a gridsearch, where a large number of candidates (parameter configurations) is first trained on a very small batch of the training data. With each step the most promisin…
-
To run LLaMA 3.1 (or similar large language models) locally, you need specific hardware requirements, especially for storage and other resources. Here's a breakdown of what you typically need:
### …