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llama-topic-modelling's Introduction

llama-topic-modelling

Analyze the data using topic modelling machine learning to group various topics in the LocalLLaMa subreddit, LocalLLaMa Subreddit.

Our research approach uses topic modelling with Latent Dirichlet Allocation (LDA) algorithm for unsupervised machine learning pipelining on r/LocalLLaMa. The pipeline collects over 1000 submission documents from the r/LocalLLaMA subreddit, then runs topic clustering on queries related-to the use cases and developer need for on-device and smaller LLaMA. The data is fetched from the Reddit API, sorted by relevance. Documents are tokened with multi-dimensional vector encoding, then dimensional reduction is applied to visualize and analyze demand for smaller, on-device applications in LocalLLaMA.

Usage/Examples

Generate output index.html file by running the following commands.

chmod +x run.sh
./run.sh

Visualize the data opening the output/index.html file in a web browser.

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