Instructions to use Chetna19/albert-base-v2_qa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Chetna19/albert-base-v2_qa_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Chetna19/albert-base-v2_qa_model")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Chetna19/albert-base-v2_qa_model") model = AutoModelForQuestionAnswering.from_pretrained("Chetna19/albert-base-v2_qa_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ca1b54c3240e5f2e6b2670c9799a0aa0d4e540e340d5805ea3464e0115384f5
- Size of remote file:
- 3.58 kB
- SHA256:
- c4e8b27058f79b4393de9f720cc7848afc6de527f2952a4a899bf7d076b3b0d1
路
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