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# rag

Retrieval augmented generation, or RAG, is an architectural approach that can improve the efficacy of large language model (LLM) applications by leveraging custom data.

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Train a QA model

Train a QA model

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Comments 1
3 min read
Export and run models with ONNX

Export and run models with ONNX

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Comments
12 min read
Train a text labeler

Train a text labeler

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2 min read
Train without labels

Train without labels

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3 min read
Distributed embeddings cluster

Distributed embeddings cluster

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5 min read
Extract text from documents

Extract text from documents

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7 min read
Translate text between languages

Translate text between languages

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Comments 4
4 min read
Run pipeline workflows

Run pipeline workflows

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6 min read
Transcribe audio to text

Transcribe audio to text

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Comments 1
3 min read
Similarity search with images
Cover image for Similarity search with images

Similarity search with images

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4 min read
Building abstractive text summaries

Building abstractive text summaries

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Comments
3 min read
Tutorial series on txtai

Tutorial series on txtai

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Comments
11 min read
Add semantic search to Elasticsearch

Add semantic search to Elasticsearch

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Comments
7 min read
txtai API Gallery

txtai API Gallery

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Comments 2
6 min read
Build an Embeddings index with Hugging Face Datasets

Build an Embeddings index with Hugging Face Datasets

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Comments 4
4 min read
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