Instructions to use tringuyen-uit/Evidence_Retrieval_model_mdeberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tringuyen-uit/Evidence_Retrieval_model_mdeberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="tringuyen-uit/Evidence_Retrieval_model_mdeberta")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("tringuyen-uit/Evidence_Retrieval_model_mdeberta") model = AutoModelForQuestionAnswering.from_pretrained("tringuyen-uit/Evidence_Retrieval_model_mdeberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("tringuyen-uit/Evidence_Retrieval_model_mdeberta")
model = AutoModelForQuestionAnswering.from_pretrained("tringuyen-uit/Evidence_Retrieval_model_mdeberta", device_map="auto")Quick Links
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="tringuyen-uit/Evidence_Retrieval_model_mdeberta")