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Finance NLP releases new demo apps and fix documentation

John Snow Labs

of Finance NLP releases new demo apps for Question Answering and Summarization tasks and fixes documentation for many models. New demo apps We release new demo apps for Question Answering and for Summarization , showing examples using the latest models of the library. Don’t forget to check our notebooks and demos.

NLP 75
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How to use audio data in LlamaIndex with Python

AssemblyAI

For this, we create a small demo application with an LLM-powered query engine that lets you load audio data and ask questions about your data. The metadata contains the full JSON response of our API with more meta information: print(docs[0].metadata) Getting Started Create a new virtual environment: # Mac/Linux: python3 -m venv venv.

Python 200
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AIs in India will need government permission before launching

AI News

It also mandates the labelling of deepfakes with permanent unique metadata or other identifiers to prevent misuse. It has been suggested that after compliance and application for permission to release a product, developers may be required to perform a demo for government officials or undergo stress testing.

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Say It Again: ChatRTX Adds New AI Models, Features in Latest Update

NVIDIA

A new update , first demoed at GTC in March, expands the power of this RTX-accelerated chatbot app with additional features and support for new models. With CLIP support in ChatRTX, users can interact with photos and images on their local devices through words, terms and phrases, without the need for complex metadata labeling.

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Logging YOLOPandas with Comet-LLM

Heartbeat

In this article you will learn how to log the YOLOPandas prompts with comet-llm, keep track of the number of tokens used in USD($), and log your metadata. link] Through the log_prompt function, the prompt, its associated response, and metadata like token usage, total tokens model, etc. You can view a demo project here.

LLM 52
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Live Meeting Assistant with Amazon Transcribe, Amazon Bedrock, and Knowledge Bases for Amazon Bedrock

AWS Machine Learning Blog

Check out the following demo to see how it works. Solution overview The LMA sample solution captures speaker audio and metadata from your browser-based meeting app (as of this writing, Zoom and Chime are supported), or audio only from any other browser-based meeting app, softphone, or audio source.

Metadata 108
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Implement unified text and image search with a CLIP model using Amazon SageMaker and Amazon OpenSearch Service

AWS Machine Learning Blog

The dataset is a collection of 147,702 product listings with multilingual metadata and 398,212 unique catalogue images. For demo purposes, we use approximately 1,600 products. There are 16 files that include product description and metadata of Amazon products in the format of listings/metadata/listings_.json.gz.