Question Answering
Transformers
Safetensors
Vietnamese
xlm-roberta
SemViQA
fact-checking
information-retrieval
Instructions to use SemViQA/infoxlm-large-isedsc01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SemViQA/infoxlm-large-isedsc01 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="SemViQA/infoxlm-large-isedsc01")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("SemViQA/infoxlm-large-isedsc01") model = AutoModelForQuestionAnswering.from_pretrained("SemViQA/infoxlm-large-isedsc01", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add link to paper and abstract to model card
#1 opened over 1 year ago
by
nielsr