Instructions to use guldasta/xtreme-MLQA.hi.hi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use guldasta/xtreme-MLQA.hi.hi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="guldasta/xtreme-MLQA.hi.hi")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("guldasta/xtreme-MLQA.hi.hi") model = AutoModelForQuestionAnswering.from_pretrained("guldasta/xtreme-MLQA.hi.hi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8b175812c4af311bbbe6c7d370876fcd0b1177e81815aa4bfaf5539bc950c3f1
- Size of remote file:
- 1.11 GB
- SHA256:
- d7a6c12c32431728770c82883ae08ffaa919365fc9c6e61fb7aae7524e0b9088
路
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