Instructions to use srcocotero/bert-large-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use srcocotero/bert-large-qa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="srcocotero/bert-large-qa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("srcocotero/bert-large-qa") model = AutoModelForQuestionAnswering.from_pretrained("srcocotero/bert-large-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f3ccff933f06b9aa3dc0d82aba6b86e117513a09babefc3de86bf7c643793903
- Size of remote file:
- 1.34 GB
- SHA256:
- 15a76e48a65205e6f4977eda5582b9ba6d03936355db095eb0037c90243e1eb5
路
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