Instructions to use krinal214/xlm-3lang with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use krinal214/xlm-3lang with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="krinal214/xlm-3lang")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("krinal214/xlm-3lang") model = AutoModelForQuestionAnswering.from_pretrained("krinal214/xlm-3lang", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ad623b44ec2eda01c92abf72629d8ba540d2e67832560d6381df4e075c2ce06
- Size of remote file:
- 1.11 GB
- SHA256:
- 5e8c4dc16ac6e845920bd04885e0b45941f51f03b135185ddeaa3807436d7336
路
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