Educational
How to Use the Starling-LM-7B-beta Model with MLX

How to Use the Starling-LM-7B-beta Model with MLX

In the fast-evolving landscape of machine learning and natural language processing (NLP), models are being improved and adapted to meet various needs. Today, we’re diving into how to use the Starling-LM-7B-beta model, freshly converted into MLX format. This can unlock...

How to Use BioMedLM 2.7B for Biomedical NLP Tasks

How to Use BioMedLM 2.7B for Biomedical NLP Tasks

The BioMedLM 2.7B is a powerful language model specifically designed for biomedical research, making it capable of performing well in various NLP tasks. In this guide, we’ll cover its usage, how it works, and troubleshooting tips to enhance your experience....

How to Use the Multilingual Sentence-Transformers Model

How to Use the Multilingual Sentence-Transformers Model

Welcome to a comprehensive guide on leveraging the power of the sentence-transformers model, specifically the stsb-xlm-r-multilingual version. This model is designed to convert sentences and paragraphs into dense vector representations for various natural language...

How to Use Sentence-Transformers for Sentence Embeddings

How to Use Sentence-Transformers for Sentence Embeddings

Sentence-transformers are powerful tools used to map sentences and paragraphs to dense vector spaces, which makes them ideal for tasks like clustering and semantic search. In this guide, we will explore how to use the sentence-transformers library, specifically using...

Unlocking the Power of Sentence Transformers

Unlocking the Power of Sentence Transformers

If you're diving into the world of semantic search or text clustering, you've likely heard of the sentence-transformers library. This powerful tool maps sentences and paragraphs to a 768-dimensional dense vector space, enabling enhanced sentence similarity...