|
Download README.md from Sediba-AI/sediba-XLM-R: direct link, hf CLI and curl.
- Browser
- Download file 3.33 kB
-
https://huggingface.co/Sediba-AI/sediba-XLM-R/resolve/main/README.md
- Command line
-
hf download hf://Sediba-AI/sediba-XLM-R/README.md
-
curl -L -o README.md https://huggingface.co/Sediba-AI/sediba-XLM-R/resolve/main/README.md
3.33 kB
| language: nso | |
| tags: | |
| - xlm-roberta | |
| - masked-language-model | |
| - sepedi | |
| - african-language | |
| - sediba | |
| - nlu | |
| - nlp | |
| license: mit | |
| # sediba-XLM-R | |
| A Sepedi masked-language model built on XLM-RoBERTa for Sepedi NLU research and token-level tasks. | |
| ## Model Details | |
| ### Model Description | |
| - **Developed by:** Sediba AI NPC | |
| - **Funded by:** Sediba AI NPC / TST (Pty) Ltd — Mankweng, Limpopo | |
| - **Shared by:** Sediba AI NPC | |
| - **Model type:** Masked language model (encoder-only Transformer) | |
| - **Language(s) (NLP):** Sepedi (engpossible code-switched Sepedi/English contexts) | |
| - **License:** MIT | |
| - **Finetuned from model:** XLM-RoBERTa-base (Facebook/Google XLM-R) | |
| ### Model Sources | |
| - **Repository:** huggingface.co/Sediba-AI/sediba-XLM-R | |
| - **Demo:** `huggingface.co/spaces/Sediba-AI/leotsha` (7-mode CDI datafication game surface) | |
| - **Paper:** [forthcoming] | |
| ## Uses | |
| ### Direct Use | |
| - Masked-token prediction and probing for Sepedi | |
| - Token-level NLU research (intent, NER probes) built on Sepedi representations | |
| - Evaluation baseline for Sepedi-language NLP tasks | |
| ### Downstream Use | |
| - Fine-tuning on Sepedi downstream tasks (classification, NER, etc.) | |
| - Serving as the Sepedi representation anchor for the broader Sediba model family | |
| ### Out-of-Scope Use | |
| - Generative/conversational Sepedi (this is an MLM, not a generative LM) | |
| - High-stakes automated decisions about Sepedi speakers without human review | |
| ## Sepedi Families Context | |
| This repo is the **Sediba Sepedi MLM anchor**. It is one model in a family with distinct roles: | |
| || Model | Role | Status | Repo / location | | |
| ||---|---|---|--|---| | |
| || **sediba-XLM-R** (this repo) | Masked-language Sepedi NLU anchor | **Shipped** | `Sediba-AI/sediba-XLM-R` on HF | | |
| || **Leotša la Sediba** | Conversational Sepedi (post-training / RLHF tier) | **Pending — publication holds until 1B+ base tier** | held in Sediba vaults; HF publication pending 1B+ base | | |
| || **SedibaLM V7** | QLoRA experiment: Qwen2.5-1.5B-Instruct + custom Sepedi vocab extension | **In training (Kaggle trail)** | Kaggle trail (`kaggle.com/sedibaai/sedibalm-v7-sepedi-qlora`) + local `v7_launch_bundle/` | | |
| **Leotša la Sediba** and SedibaLM V7 are **not** published under this repo ID. They are tracked separately in Sediba's vaults and training pipeline, and differ from this model in base architecture, parameter tier, and task. | |
| ## Evaluation | |
| - Self-language sanity probe via lglang on a held-out Sepedi sample | |
| - Sepedi-width fertility check comparing model output diversity against a Sepedi baseline sample | |
| - Exact results are tracked in the Sediba vaults (model evaluation log) and are available on request. | |
| ## Limitations | |
| - Single-language Sepedi focus; performance on heavily code-switched or multi-register Sepedi is not fully characterised | |
| - Masked-LM only — not a generative model; do not use for Sepedi text generation | |
| - Training data scope and provenance are tracked in Sediba's data-governance stack (Esethu / NOODL / Itsebe) and the Sepedi corpus register | |
| ## Citation | |
| If you use this model, cite Sediba AI NPC and link the repo: | |
| ``` | |
| @misc{sediba-xlmr, | |
| author = {Sediba AI NPC}, | |
| title = {sediba-XLM-R: A Sepedi masked-language model built on XLM-RoBERTa}, | |
| year = {2026}, | |
| url = {https://huggingface.co/Sediba-AI/sediba-XLM-R} | |
| } | |
| ``` | |
| Build by Sediba AI | Mankweng, Limpopo. | |