Fast_Sentence_Embeddings
gensim
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Fast_Sentence_Embeddings | gensim | |
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2 | 18 | |
603 | 15,125 | |
- | 1.0% | |
0.0 | 7.5 | |
about 1 year ago | 28 days ago | |
Jupyter Notebook | Python | |
GNU General Public License v3.0 only | GNU Lesser General Public License v3.0 only |
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Fast_Sentence_Embeddings
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You probably shouldn't use OpenAI's embeddings
You can find some comparisons and evaluation datasets/tasks here: https://www.sbert.net/docs/pretrained_models.html
Generally MiniLM is a good baseline. For faster models you want this library:
https://github.com/oborchers/Fast_Sentence_Embeddings
For higher quality ones, just take the bigger/slower models in the SentenceTransformers library
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[D] Unsupervised document similarity state of the art
Links: fse: https://github.com/oborchers/Fast_Sentence_Embeddings Sentence-transformers: https://github.com/oborchers/sentence-transformers
gensim
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Understanding How Dynamic node2vec Works on Streaming Data
This is our optimization problem. Now, we hope that you have an idea of what our goal is. Luckily for us, this is already implemented in a Python module called gensim. Yes, these guys are brilliant in natural language processing and we will make use of it. 🤝
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Is it home bias or is data wrangling for machine learning in python much less intuitive and much more burdensome than in R?
Standout python NLP libraries include Spacy and Gensim, as well as pre-trained model availability in Hugginface. These libraries have widespread use in and support from industry and it shows. Spacy has best-in-class methods for pre-processing text for further applications. Gensim helps you manage your corpus of documents, and contains a lot of different tools for solving a common industry task, topic modeling.
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Topic modelling with Gensim and SpaCy on startup news
For the topic modelling itself, I am going to use Gensim library by Radim Rehurek, which is very developer friendly and easy to use.
- Unsupervised Learning for String Matching in Python - can I have advice on how to go about this?
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How to build a search engine with word embeddings
We will be using gensim to load our Google News pre-trained word vectors. Find the code for this here.
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The Levenshtein Distance in Production
> Problem statement: the Levenshtein distance is a string metric for measuring the difference between two sequences
Another variant is "I have a bunch of words (a dictionary) and one query word, and want to find all words from the dictionary that are close to the query word".
This leads to an interesting class of problems, because you can do clever things where you precompute search structures (Levenshtein automata [0]) from the dictionary. The similarity queries then run (much) faster – in production, performance matters.
We recently merged a PR like that into Gensim [1].
This gave a ~1,500x speed-up compared to naively comparing all pairwise strings with Levenshtein distance. A difference between the training step running for years (=unusable) and minutes.
[0] http://blog.notdot.net/2010/07/Damn-Cool-Algorithms-Levensht...
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Koan: A word2vec negative sampling implementation with correct CBOW update
Apparently it did: https://github.com/RaRe-Technologies/gensim/issues/1873
What are some alternatives?
BERTopic - Leveraging BERT and c-TF-IDF to create easily interpretable topics.
scikit-learn - scikit-learn: machine learning in Python
MLflow - Open source platform for the machine learning lifecycle
tensorflow - An Open Source Machine Learning Framework for Everyone
Keras - Deep Learning for humans
flair - A very simple framework for state-of-the-art Natural Language Processing (NLP)
fuzzywuzzy - Fuzzy String Matching in Python
GuidedLDA - semi supervised guided topic model with custom guidedLDA
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
gym - A toolkit for developing and comparing reinforcement learning algorithms.
pdpipe - Easy pipelines for pandas DataFrames.