In this project, I explored how local LLMs can be used to label data and support analyses. Specifically, I used Llama2 model to automatically categorise my bank transaction data.
thu-vu92/local-llms-analyse-finance 排名第 12,985，有 876 个星标。
thu-vu92/local-llms-analyse-finance 排名第 12,985，此处有 8 个同类条目；elviswf/DeepLearningBookQA_cn 排名第 12,987。
| 名称 | 排名 | 指标 |
|---|---|---|
| openai/openai-responses-starter-app | 12,963 |
|
| ritchieng/deep-learning-wizard | 12,964 |
|
| Edward1Chou/SentimentAnalysis | 12,972 |
|
| joelgrus/fizz-buzz-tensorflow | 12,979 |
|
| elviswf/DeepLearningBookQA_cn | 12,987 |
|
| xianyu110/clawbot | 12,992 |
|
| utkuozbulak/pytorch-custom-dataset-examples | 12,999 |
|
| harryzhangOG/Deep-RL-Notes | 13,003 |
|
| 参数 | 值 |
|---|---|
| 语言 | Jupyter Notebook |
| 类别 | Tutorials |
| 子类别 | Tool-specific tutorials |
| 星标数 | 876 |
| 分叉数 | 240 |
| 贡献者 | 1 |
| 创建日期 | 2024-02-02 |
| 更新日期 | 2026-10-03 |
| 1 天星标数 | 0 |
| 7 天星标数 | 0 |
| 排名 | 12,985 |
| 上次排名 | 12,880 |
| 排名变化 | -105 |
| 7 天星标排名 | 13,705 |
| 上次 7 天星标排名 | 13,718 |
| 7 天星标排名变化 | 13 |
| 总星标排名 | 12,368 |
| 上次总星标排名 | 12,349 |
| 总星标排名变化 | -19 |
local-llms-analyse-finance In this project, I explored how local LLMs can be used to label data and support analyses. Specifically, I used Llama2 model to automatically categorise my bank transaction data. Installing local LLMs with Ollama (currently support MacOS and Linux) Tutorial video: Personal finance dashboard: Disclaimer: The example data in this repo are fictious and for illustration purposes.
thu-vu92/local-llms-analyse-finance 有 876 个星标和 240 个分叉。
thu-vu92/local-llms-analyse-finance 排名第 12,985。
thu-vu92/local-llms-analyse-finance 有 876 个星标，语言为 Jupyter Notebook，类别为 Tutorials。
thu-vu92/local-llms-analyse-finance 与 elviswf/DeepLearningBookQA_cn 比较，后者排名第 12,987，有 875 个星标。
In this project, I explored how local LLMs can be used to label data and support analyses. Specifically, I used Llama2 model to automatically categorise my bank transaction data.
https://www.youtube.com/watch?v=h_GTxRFYETY
The example data in this repo are fictious and for illustration purposes.