Instructions to use Forturne/qa_roberta_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Forturne/qa_roberta_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Forturne/qa_roberta_1")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Forturne/qa_roberta_1") model = AutoModelForQuestionAnswering.from_pretrained("Forturne/qa_roberta_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 05ec0b3740b533a888af51d78f49f261ab79e229341f49573be11107d15b54b0
- Size of remote file:
- 1.34 GB
- SHA256:
- a39721dd0f02470ecfc47f37042e99a81cb0a5573414637e788cffafa686f1ae
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.