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| Natura: | Recurso digital |
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Zenodo
2026
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| Accesso online: | https://doi.org/10.5281/zenodo.19332921 |
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| _version_ | 1866901851427831808 |
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| author | Schweinberger, Martin |
| author_facet | Schweinberger, Martin |
| contents | This tutorial introduces the use of local large language models (LLMs) in R via the Ollama platform and the ollamar package, covering installation and setup, the generate() and chat() functions, and prompt engineering for text analysis tasks including summarisation, classification, and question answering. It is aimed at researchers in linguistics and digital humanities who want to apply LLMs to their data without sending sensitive information to external APIs. This tutorial is part of the Language Technology and Data Analysis Laboratory (LADAL), a free, open-access research infrastructure at the University of Queensland. LADAL provides tutorials, tools, and courses for researchers working with language data. All materials are freely available at https://ladal.edu.au and are part of the Language Data Commons of Australia (LDaCA), funded by ARDC and NCRIS. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19332921 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Local Large Language Models in R with Ollama Schweinberger, Martin LADAL language technology open educational resource University of Queensland corpus linguistics text analysis R large language models LLM Ollama ollamar local AI privacy-preserving NLP text generation prompt engineering This tutorial introduces the use of local large language models (LLMs) in R via the Ollama platform and the ollamar package, covering installation and setup, the generate() and chat() functions, and prompt engineering for text analysis tasks including summarisation, classification, and question answering. It is aimed at researchers in linguistics and digital humanities who want to apply LLMs to their data without sending sensitive information to external APIs. This tutorial is part of the Language Technology and Data Analysis Laboratory (LADAL), a free, open-access research infrastructure at the University of Queensland. LADAL provides tutorials, tools, and courses for researchers working with language data. All materials are freely available at https://ladal.edu.au and are part of the Language Data Commons of Australia (LDaCA), funded by ARDC and NCRIS. |
| title | Local Large Language Models in R with Ollama |
| topic | LADAL language technology open educational resource University of Queensland corpus linguistics text analysis R large language models LLM Ollama ollamar local AI privacy-preserving NLP text generation prompt engineering |
| url | https://doi.org/10.5281/zenodo.19332921 |