Instructions to use FredDYyy/XLM_R_Extractive_QA_Vi_En_Zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FredDYyy/XLM_R_Extractive_QA_Vi_En_Zh with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="FredDYyy/XLM_R_Extractive_QA_Vi_En_Zh")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("FredDYyy/XLM_R_Extractive_QA_Vi_En_Zh") model = AutoModelForQuestionAnswering.from_pretrained("FredDYyy/XLM_R_Extractive_QA_Vi_En_Zh", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened about 3 years ago
by
SFconvertbot