Tsdae Alternatives
Similar projects and alternatives to tsdae based on common topics and language
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happy-transformer
Happy Transformer makes it easy to fine-tune and perform inference with NLP Transformer models.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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haystack
:mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
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tsdae reviews and mentions
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Tranformer-based Denoising AutoEncoder for ST Unsupervised pre-training
A new PyPI package for training sentence embedding models in just 2 lines.
The acquisition of sentence embeddings often necessitates a substantial volume of labeled data. However, in many cases and fields, labeled data is rarely accessible, and the procurement of such data is costly. In this project, we employ an unsupervised process grounded in pre-trained Transformers-based Sequential Denoising Auto-Encoder (TSDAE), introduced by the Ubiquitous Knowledge Processing Lab of Darmstadt, which can realize a performance level reaching 93.1% of in-domain supervised methodologies.
The TSDAE schema comprises two components: an encoder and a decoder. Throughout the training process, TSDAE translates tainted sentences into uniform-sized vectors, necessitating the decoder to reconstruct the original sentences utilizing this sentence embedding. For good reconstruction quality, the semantics must be captured well in the sentence embeddings from the encoder. Subsequently, during inference, the encoder is solely utilized to form sentence embeddings.
GitHub : https://github.com/louisbrulenaudet/tsdae
Installation :
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louisbrulenaudet/tsdae is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of tsdae is Python.
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