Instructions to use mrm8488/bert-small-finetuned-squadv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/bert-small-finetuned-squadv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="mrm8488/bert-small-finetuned-squadv2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("mrm8488/bert-small-finetuned-squadv2") model = AutoModelForQuestionAnswering.from_pretrained("mrm8488/bert-small-finetuned-squadv2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f3e6bfc998841c454850d978f915e656f89743f6021966c0040fe8211f526c51
- Size of remote file:
- 114 MB
- SHA256:
- 23dec91ce94b5f8ee55106c10ee5ab350a13b891ba1feab5bd90ed62ae6896cd
路
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