Question Answering
Transformers
Safetensors
Tigrinya
extractive-qa
xlm-roberta
vexmlm
geez
low-resource
Instructions to use Hailay/VEXMLM-TiQuAD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hailay/VEXMLM-TiQuAD with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="Hailay/VEXMLM-TiQuAD")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Hailay/VEXMLM-TiQuAD", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Align model card text with the corrected paper
Verified signatureText only; no metric changed. New paper title and co-author name in the citation; QA scores described as development-split results; pretraining-data statement corrected; loss/perplexity pairing clarified.40c28f7
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Add VEXMLM-TiQuAD: five verified fine-tuned checkpoints (seeds 42-46)
Verified signaturee0c0cb0