Extracting-Training-Data-from-Large-Langauge-Models
Neural-Scam-Artist
| Extracting-Training-Data-from-Large-Langauge-Models | Neural-Scam-Artist | |
|---|---|---|
| 1 | 2 | |
| 26 | 23 | |
| - | - | |
| 5.1 | 0.0 | |
| almost 2 years ago | over 2 years ago | |
| Python | Python | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Extracting-Training-Data-from-Large-Langauge-Models
-
Paper Implementation - Extracting Training Data from Large Language Models
Code - https://github.com/shreyansh26/Extracting-Training-Data-from-Large-Langauge-Models
Neural-Scam-Artist
What are some alternatives?
funcbygpt - tell the function what to do and gpt will write the code
datasketch - MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble and HNSW
finetune-gpt2xl - Guide: Finetune GPT2-XL (1.5 Billion Parameters) and finetune GPT-NEO (2.7 B) on a single GPU with Huggingface Transformers using DeepSpeed
bertviz - BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
LSH - Locality Sensitive Hashing using MinHash in Python/Cython to detect near duplicate text documents
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Transformers4Rec - Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.
intertext - Detect and visualize text reuse
tasksource - Datasets collection and preprocessings framework for NLP extreme multitask learning