--- title: Sinhala MMLU Shared Task - ICTer 2026 emoji: 📚 colorFrom: indigo colorTo: purple sdk: static pinned: false thumbnail: >- https://cdn-uploads.huggingface.co/production/uploads/6aacdff7696e33219803d7b3/W3V105cav8y0nHZS9hrDd.png short_description: Sinhala MMLU Shared Task submissions - ICTer 2026 license: other --- # Sinhala MMLU Shared Task — ICTer 2026 Official submission organisation for the **Sinhala MMLU Shared Task** at ICTer 2026, Colombo, Sri Lanka. **[Task website](https://sinhalammlu.ucsc.cmb.ac.lk)** ## For participating teams Registered teams upload their final system here **after the Codabench leaderboard closes on 22 October 2026**. Do not upload before that date. One repository per team, named `team-`, containing: - `README.md` - model card and reproduction manifest (copy `team-template`) - `run.sh` - turns the released test file into `predictions.jsonl` - `requirements.txt` - pinned versions, or a Dockerfile - `src/` - your code - trained weights, in this repo or a linked one Trained weights are uploaded to this organisation as model repositories. The adapter if you trained one, full weights if you fine-tuned the whole model, and nothing if you used an open model unchanged. Do not re-upload unmodified base models. Start by duplicating **`team-template`**, which has the required structure and the model card to fill in. ## What to upload Upload what you trained, not what you downloaded: | Your situation | Upload | |---|---| | No training. Open model used as-is | Nothing. Name the model id and commit in your card. | | LoRA or other adapter | The adapter only. | | Full fine-tune or merged model | The full weights. | | Ensemble | One repository per trained component. | ## Joining Register your team [here](https://forms.gle/atqsMX6kPn18BDoP9) to participate. Questions: **sinhalammlu.icter2026@gmail.com**