- create a custom base image for a Cloud Workstation environment using a Dockerfile
. Uses:
Quantized models from
The "LLM" toolkit offers a versatile command-line utility and Python library that allows users to work efficiently with large language models. Users can execute prompts directly from their terminals, store the outcomes in SQLite databases, generate embeddings, and perform various other tasks. In this extensive tutorial, topics covered include setup, usage, OpenAI models, alternative models, embeddings, plugins, model aliases, Python APIs, prompt templates, logging, related tools, CLI references, contributing, and change logs.
train models for processing documents based on specific needs and requirements. It offers capabilities such as entity recognition, key information extraction, and data validation,
Explore the architecture of TiDE and apply it in a forecasting project using Python
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