- Machine Learning: other versions:
- What is Elastic Machine Learning?
- Setup and security
- Anomaly detection
- Finding anomalies
- Advanced concepts
- API quick reference
- Examples
- Tutorial: Getting started with anomaly detection
- Generating alerts for anomaly detection jobs
- Aggregating data for faster performance
- Customizing detectors with custom rules
- Detecting anomalous categories of data
- Detecting anomalous locations in geographic data
- Performing population analysis
- Altering data in your datafeed with runtime fields
- Adding custom URLs to machine learning results
- Handling delayed data
- Mapping anomalies by location
- Exporting and importing machine learning jobs
- Resources
- Data frame analytics
- Natural language processing
Third party NLP models
editThird party NLP models
editThe Elastic Stack machine learning features support transformer models that conform to the standard BERT model interface and use the WordPiece tokenization algorithm.
The current list of supported architectures is:
- BERT
- DPR bi-encoders
- DistilBERT
- ELECTRA
- MobileBERT
- RetriBERT
- MPNet
- SentenceTransformers bi-encoders with the above transformer architectures
In general, any trained model that has a supported architecture is deployable in Elasticsearch by using eland. However, it is not possible to test every third party model. The following lists are therefore provided for informational purposes only and may not be current. Elastic makes no warranty or assurance that the machine learning features will continue to interoperate with these third party models in the way described, or at all.
These models are listed by NLP task; for more information about those tasks, refer to Overview.
Third party fill-mask models
editThird party named entity recognition models
editThird party text embedding models
editUsing SentenceTransformerWrapper:
- https://huggingface.co/sentence-transformers/all-MiniLM-L12-v2
- https://huggingface.co/sentence-transformers/LaBSE
- https://huggingface.co/sentence-transformers/msmarco-distilbert-base-tas-b
- https://huggingface.co/sentence-transformers/msmarco-MiniLM-L-12-v3
- https://huggingface.co/sentence-transformers/nli-bert-base-cls-pooling
- https://huggingface.co/sentence-transformers/bert-base-nli-cls-token
- https://huggingface.co/sentence-transformers/facebook-dpr-ctx_encoder-multiset-base
- https://huggingface.co/sentence-transformers/facebook-dpr-question_encoder-single-nq-base
- https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2
Using DPREncoderWrapper:
- https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base
- https://huggingface.co/facebook/dpr-question_encoder-single-nq-base
- https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base
- https://huggingface.co/facebook/dpr-question_encoder-multiset-base
- https://huggingface.co/castorini/ance-dpr-context-multi
- https://huggingface.co/castorini/ance-dpr-question-multi
- https://huggingface.co/castorini/bpr-nq-ctx-encoder
- https://huggingface.co/castorini/bpr-nq-question-encoder
Third party text classification models
edit- https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english
- https://huggingface.co/bhadresh-savani/distilbert-base-uncased-emotion
- https://huggingface.co/Hate-speech-CNERG/dehatebert-mono-english
- https://huggingface.co/ProsusAI/finbert
- https://huggingface.co/nateraw/bert-base-uncased-emotion
Third party zero-shot text classification models
editOn this page