Deep Learning, NLP, NMT, AI, ML
Tracing instruction in lldb debugger.just a python-script for lldb. How to use it? Break at an address where you want to begin tracing. Import lldb python script. Set an address where you want to end tracing. Use ‘trace’ command,and redirect log to file. trace -e 0x111111 -l all -t ~/tracelog.txt -d ~/debuglog.txt GitHub https://github.com/yangyss/lldb-trace
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ARTIF ARTIF is a new advanced real time threat intelligence framework built that adds another abstraction layer on the top of MISP to identify threats and malicious web traffic on the basis of IP reputation and historical data. It also performs automatic enrichment and threat scoring by collecting, processing and correlating observables based on different factors. Key features of ARTIF includes:- Scoring System: Enriches IP addresses with threat metadata including a threat score which can act as a threshold value […]
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Graph Transformer – Pytorch Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2. This was recently used by both Costa et al and Bakers lab for transforming MSA and pair-wise embedding into 3d coordinates. Todo add rotary embeddings for injecting adjacency information Install $ pip install graph-transformer-pytorch Usage import torch from graph_transformer_pytorch import GraphTransformer model = GraphTransformer( dim = 256, depth = 6, edge_dim = 512, # optional – if left out, edge dimensions is assumed to […]
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rasa-travel-chatbot Here is my Senior Design Project that I implemented to graduate from Computer Engineering. It is a chatbot made in RASA and helps the user to plan their vacation in the Turkish language. In order to plan the user’s vacation, it provides reservations by asking various questions for hotel, flight, or event. Create a virtual environment of python 3.6 or greater. Navigate to the rasa directory. Run the command:rasa train After the model is trained, launch the rasa core […]
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BoB This repository provides the implementation details for the ACL 2021 main conference paper: BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data. 1. Data Preparation In this work, we carried out persona-based dialogue generation experiments under a persona-dense scenario (English PersonaChat) and a persona-sparse scenario (Chinese PersonalDialog), with the assistance of a series of auxiliary inference datasets. Here we summarize the key information of these datasets and provide the links to download these datasets if […]
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Image-to-ASCII Convert any image into greyscale ASCII art. Setup 1. Clone Repo git clonehttps://github.com/BSmith156/Image-to-ASCII.git 2. Install Requirements pip install -r requirements.txt Usage image_to_ascii.py input_file output_file [-i] [-max n] Arguments Argument Description input_file The image file being converted. output_file The file to store the ASCII art. -i Optional. Inverts the image colour, useful when displaying the output using a light font on a dark background. -max n Optional. Sets the maximum width/height of the output to n, 0 for no maximum. […]
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DensePhrases DensePhrases is an extractive phrase search tool based on your natural language inputs. From 5 million Wikipedia articles, it can search phrase-level answers to your questions or find related entities to (subject, relation) pairs in real-time. Due to the extractive nature of DensePhrases, it always provides an evidence passage for each phrase. Please see our paper Learning Dense Representations of Phrases at Scale (Lee et al., 2021) for more details. Installation # Install torch with conda (please check your […]
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HoroPCA This code is the official PyTorch implementation of the ICML 2021 paper: HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical ProjectionsInes Chami*, Albert Gu*, Dat Nguyen*, Christopher RéStanford UniversityPaper: https://arxiv.org/abs/2106.03306 Abstract. This paper studies Principal Component Analysis (PCA) for data lying in hyperbolic spaces. Given directions, PCA relies on: (1) a parameterization of subspaces spanned by these directions, (2) a method of projection onto subspaces that preserves information in these directions, and (3) an objective to optimize, namely the variance explained […]
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DeepCDR Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network This work has been accepted to ECCB2020 and was also published in the journal Bioinformatics. DeepCDR is a hybrid graph convolutional network for cancer drug response prediction. It takes both multi-omics data of cancer cell lines and drug structure as inputs and predicts the drug sensitivity (binary or contineous IC50 value). Keras==2.1.4 TensorFlow==1.13.1 hickle >= 2.1.0 DeepCDR can be downloaded by git clone https://github.com/kimmo1019/DeepCDR Installation has been tested in […]
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meerkat Meerkat provides fast and flexible data structures for working with complex machine learning datasets. Getting started pip install meerkat-ml Note: some parts of Meerkat rely on optional dependencies. If you know which optional dependencies you’d like to install, you can do so using something like pip install meerkat-ml[dev,text] instead. See setup.py for a full list of optional dependencies. Load your dataset into a DataPanel and get going! import meerkat as mk dp = mk.DataPanel.from_csv(“…”) What is Meerkat? Meerkat makes […]
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