nuprl/MultiPL-T
MultiPL-T Fine-Tuning Datasets This dataset contains the MultiPL-T fine-tuning sets described in the paper "Knowledge Transfer from High-Resource to Low-Resource Programming Languages for Code LLMs": Arxiv. In short, it contains fine-tuning datasets for Julia, Lua, Racket, OCaml, and R. Citation If you use this dataset we request that you cite our work: @article{cassano:multipl-t, title = {Knowledge {{Transfer}} from {{High-Resource}} to {{Low-Resource… See the full description on the dataset page: https://huggingface.co/datasets/nuprl/MultiPL-T.
| Author / organization | nuprl |
|---|---|
| License (as declared) | bigcode-openrail-m |
| Downloads | 239 (as reported by Hugging Face) |
| Likes | 9 |
| Created | 17 August 2023 |
| Last updated at source | 20 August 2024 |
Popularity, last 2 days
239 now (-1 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Connected in the knowledge graph
- mradermacher/MultiPL-T-CodeLlama_34b-GGUFModel · used to train
- mradermacher/MultiPL-T-CodeLlama_34b-i1-GGUFModel · used to train
- mradermacher/MultiPL-T-StarCoderBase_15b-i1-GGUFModel · used to train
- nuprl/MultiPL-T-StarCoderBase_1bModel · used to train
- mradermacher/MultiPL-T-DeepSeekCoder_33b-GGUFModel · used to train
- mradermacher/MultiPL-T-CodeLlama_70b-i1-GGUFModel · used to train
- mradermacher/MultiPL-T-StarCoderBase_15b-GGUFModel · used to train
- mradermacher/MultiPL-T-CodeLlama_70b-GGUFModel · used to train
- mradermacher/MultiPL-T-DeepSeekCoder_33b-i1-GGUFModel · used to train
Recent changes
- 17 Oct 2026 Description: MultiPL-T Fine-Tuning Datasets This dataset contains the MultiPL-T fine-tuning sets described in the paper "Knowledge Transfer from High-Resource to Low-Resource Programming Languages for Code LLMs": Arxiv. In short, it contains fine-tuning → MultiPL-T Fine-Tuning Datasets This dataset contains the MultiPL-T fine-tuning sets described in the paper "Knowledge Transfer from High-Resource to Low-Resource Programming Languages for Code LLMs": Arxiv. In short, it contains fine-tuning
Changes detected by Silytics between refreshes of the source.
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