Instructions to use aravind-812/roberta-train-json with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aravind-812/roberta-train-json with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="aravind-812/roberta-train-json")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("aravind-812/roberta-train-json") model = AutoModelForQuestionAnswering.from_pretrained("aravind-812/roberta-train-json") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91a8f0dc0cdbff9d7c67f3abb731e3e201dfd292d8d5e50355141cc46442d2af
- Size of remote file:
- 1.42 GB
- SHA256:
- 2244f3818ba8fac43eb95405ecb1da1c26c818b3dcaad7cc22145459b6c20804
路
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