DNABERT
datasets
| DNABERT | datasets | |
|---|---|---|
| 1 | 15 | |
| 546 | 18,480 | |
| - | 1.2% | |
| 3.1 | 9.5 | |
| 2 months ago | 4 days ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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DNABERT
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[D] New to DNABERT
If I want to get started, they said it's optional to pre-train (so you can skip to step 3). This is where I got tripped up: "Note that the sequences are in kmer format, so you will need to convert your sequences into that." From what I understand, you need to do this so that all of the sequences are the same length? So kmer=6 means all of the sequences are length 6? Someone suggested that I take the first nucleotide in the promoter and grab 3 nucleotides before and 3 nucleotides after (+/-3 bases). I don't think that's how the kmer thing works though? I tried replicating how I think it works down below (I got confused on the last row of the 'after' df). Please correct me if I'm wrong!
datasets
- 🐍🐍 23 issues to grow yourself as an exceptional open-source Python expert 🧑💻 🥇
- Mastering ROUGE Matrix: Your Guide to Large Language Model Evaluation for Summarization with Examples
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How to Train Large Models on Many GPUs?
https://github.com/huggingface/datasets
https://github.com/huggingface/transformers
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[D] Can we use Ray for distributed training on vertex ai ? Can someone provide me examples for the same ? Also which dataframe libraries you guys used for training machine learning models on huge datasets (100 gb+) (because pandas can't handle huge data).
https://huggingface.co/docs/datasets backed with an Arrow file or buffer
- Need help with a data science project
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Is there a text evaluation metric that does not need reference text?
I'm looking for an automatic evaluation metric that can score the first text higher (since it's more grammatically correct/better for other reasons). All the metrics for NLG I found require some reference text to match the generated text with, which I don't have.
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FauxPilot – an open-source GitHub Copilot server
And then pass that my_code.json as the dataset name.
[1] https://github.com/huggingface/datasets
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Hugging Face Introduces ‘Datasets’: A Lightweight Community Library For Natural Language Processing (NLP)
Code for https://arxiv.org/abs/2109.02846 found: https://github.com/huggingface/datasets
Quick Read | Paper | Github
- Datasets: A Community Library for Natural Language Processing
What are some alternatives?
courses - This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI)
sentence-transformers - Multilingual Sentence & Image Embeddings with BERT
Stanza - Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
datumaro - Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.
stanford-tensorflow-tutorials - This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
cypress-realworld-app - A payment application to demonstrate real-world usage of Cypress testing methods, patterns, and workflows.
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
edex-ui - A cross-platform, customizable science fiction terminal emulator with advanced monitoring & touchscreen support.
nlp-recipes - Natural Language Processing Best Practices & Examples
first-contributions - 🚀✨ Help beginners to contribute to open source projects
bioconvert - Bioconvert is a collaborative project to facilitate the interconversion of life science data from one format to another.
frankmocap - A Strong and Easy-to-use Single View 3D Hand+Body Pose Estimator