Natural language processing

Natural language processing (NLP) is a field of computer science that studies how computers and humans interact. In the 1950s, Alan Turing published an article that proposed a measure of intelligence, now called the Turing test. More modern techniques, such as deep learning, have produced results in the fields of language modeling, parsing, and natural-language tasks.

🚀 Feature request

Fast Tokenizer for DeBERTA-V3 and mDeBERTa-V3

Motivation

DeBERTa V3 is an improved version of DeBERTa. With the V3 version, the authors also released a multilingual model "mDeBERTa-base" that outperforms XLM-R-base. However, DeBERTa V3 currently lacks a FastTokenizer implementation which makes it impossible to use with some of the example scripts (They require a Fa

We at Jina are fans of the written word. And , if you are a beginner in neural search and OSS, what better than starting out with documentation and blogs ?
How to make a contribution?

Comment below this issue the topic you have in mind for writing a blog. The topic should revolve around - neural search/Jina/Jina-OSS etc. (basically about Jina)

What can it be about? It could be a tutorial or

In gensim/models/fasttext.py:

    model = FastText(
        vector_size=m.dim,
        vector_size=m.dim,
        window=m.ws,
        window=m.ws,
        epochs=m.epoch,
        epochs=m.epoch,
        negative=m.neg,
        negative=m.neg,
        # FIXME: these next 2 lines read in unsupported FB FT modes (loss=3 softmax or loss=4 onevsall,
        # or model=3 supervi

Is your feature request related to a problem? Please describe.
I typically used compressed datasets (e.g. gzipped) to save disk space. This works fine with AllenNLP during training because I can write my dataset reader to load the compressed data. However, the predict command opens the file and reads lines for the Predictor. This fails when it tries to load data from my compressed files.

Rather than simply caching nltk_data until the cache expires and it's forced to re-download the entire nltk_data, we should perform a check on the index.xml which refreshes the cache if it differs from some previous cache.

I would advise doing this in the same way that it's done for requirements.txt:
https://github.com/nltk/nltk/blob/59aa3fb88c04d6151f2409b31dcfe0f332b0c9ca/.github/wor

Dec	JAN	Feb
	11
2021	2022	2023

Natural language processing

Here are 17,252 public repositories matching this topic...

huggingface / transformers

🚀 Feature request

Motivation

apachecn / AiLearning

google-research / bert

hankcs / HanLP

explosion / spaCy

oxford-cs-deepnlp-2017 / lectures

RasaHQ / rasa

virgili0 / Virgilio

jina-ai / jina

RaRe-Technologies / gensim

keon / awesome-nlp

bharathgs / Awesome-pytorch-list

huggingface / datasets

flairNLP / flair

NLP-LOVE / ML-NLP

allenai / allennlp

nltk / nltk

spencermountain / compromise

chiphuyen / stanford-tensorflow-tutorials

graykode / nlp-tutorial

hanxiao / bert-as-service

botpress / botpress

stanfordnlp / CoreNLP

sloria / TextBlob

ashishpatel26 / 500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code

PaddlePaddle / PaddleHub

brightmart / text_classification

brightmart / nlp_chinese_corpus

crownpku / Awesome-Chinese-NLP

ymcui / Chinese-BERT-wwm