stopes
LASER
stopes | LASER | |
---|---|---|
1 | 5 | |
238 | 3,538 | |
1.7% | 0.8% | |
5.8 | 5.7 | |
5 months ago | 14 days ago | |
Python | Jupyter Notebook | |
MIT License | GNU General Public License v3.0 or later |
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stopes
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[D] Hey Reddit! We're a bunch of research scientists and software engineers and we just open sourced a new state-of-the-art AI model that can translate between 200 different languages. We're excited to hear your thoughts so we're hosting an AMA on 07/21/2022 @ 9:00AM PT. Ask Us Anything!
We have a bunch! The model and data are available here: https://github.com/facebookresearch/fairseq/tree/nllb/examples/nllb/modeling , LASER3 here: https://github.com/facebookresearch/fairseq/tree/nllb/examples/nllb/laser\_distillation , training data here: https://github.com/facebookresearch/fairseq/tree/nllb/examples/nllb/data , FLORES and our other human translated datasets here: https://github.com/facebookresearch/flores , and an entire modular pipeline for data cleaning here: https://github.com/facebookresearch/stopes. It's also available on HuggingFace! [angela]
LASER
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SentenceTransformers: Python framework for sentence, text and image embeddings
I'm curious how people are handling multi-lingual embeddings.
I've found LASER[1] which originally had the idea to embed all languages in the same vector space, though it's a bit harder to use than models available through SentenceTransformers. LASER2 stuck with this approach, but LASER3 switched to language-specific models. However, I haven't found benchmarks for these models, and they were released about 2 years ago.
Another alternative would be to translate everything before embedding, which would introduce some amount of error, though maybe it wouldn't be significant.
1. https://github.com/facebookresearch/LASER
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[D] Hey Reddit! We're a bunch of research scientists and software engineers and we just open sourced a new state-of-the-art AI model that can translate between 200 different languages. We're excited to hear your thoughts so we're hosting an AMA on 07/21/2022 @ 9:00AM PT. Ask Us Anything!
You can check out some of our materials and open sourced artifacts here: - Our latest blog post: https://ai.facebook.com/blog/nllb-200-high-quality-machine-translation - Project Overview: https://ai.facebook.com/research/no-language-left-behind/ - Product demo: https://nllb.metademolab.com/ - Research paper: https://research.facebook.com/publications/no-language-left-behind - NLLB-200: https://github.com/facebookresearch/fairseq/tree/nllb - FLORES-200: https://github.com/facebookresearch/flores - LASER3: https://github.com/facebookresearch/LASER Joining us today for the AMA are: - Angela Fan (AF), Research Scientist - Jean Maillard (JM), Research Scientist - Maha Elbayad (ME), Research Scientist - Philipp Koehn (PK), Research Scientist - Shruti Bhosale (SB), Software Engineer We’ll be here from 07/21/2022 @09:00AM PT - 10:00AM PT Thanks and we’re looking forward to answering your questions!
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School project : sentiments analysis with my country Arabic Dialect
This may be helpful: https://github.com/facebookresearch/LASER
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[P] Bilingual text alignment tools for NMT - help needed
Check FB's LASER: https://github.com/facebookresearch/LASER/tree/master/tasks/CCMatrix Also , Sentence-Transformers has a pretty neat model for crosslingual sentence similarity: https://huggingface.co/sentence-transformers/stsb-xlm-r-multilingual
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Help with aligned word embeddings
You want LASER its a superbig model trained on tons of languages you can use it with sentence_transformers in python to compute embedings. Then you can use faiss or datasketch to find matches at K
What are some alternatives?
NeMo - A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
MUSE - A library for Multilingual Unsupervised or Supervised word Embeddings
tm2tb - Bilingual term extractor
electra - ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
flores - Facebook Low Resource (FLoRes) MT Benchmark
Arraymancer - A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends
nematus - Open-Source Neural Machine Translation in Tensorflow
fairseq - Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Thirukkural-English-Translation-Dataset - Thirukural in English