Instructions to use mateiaass/albert-base-qa-coQA-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mateiaass/albert-base-qa-coQA-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="mateiaass/albert-base-qa-coQA-3")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("mateiaass/albert-base-qa-coQA-3") model = AutoModelForQuestionAnswering.from_pretrained("mateiaass/albert-base-qa-coQA-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0abe585e84866fe06e5e5b33c5128ce7769459fa825f9f3fd65eb620b23072b0
- Size of remote file:
- 4.54 kB
- SHA256:
- 79cf866b2bb8b3db1af4225f46d729408ae1b8b4fbe7e487c0ac89a2da473616
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.