Instructions to use twmkn9/albert-base-v2-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use twmkn9/albert-base-v2-squad2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="twmkn9/albert-base-v2-squad2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("twmkn9/albert-base-v2-squad2") model = AutoModelForQuestionAnswering.from_pretrained("twmkn9/albert-base-v2-squad2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2912a2ea598f7db8cc229ec8b0b396938173b7398e5805bdd251716e0e5babff
- Size of remote file:
- 46.7 MB
- SHA256:
- 2332fa62f43189b718a62ba16a7c8c5dffa3139ee34e57f29191c489cc6fd8f1
路
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