Instructions to use deepset/tinyroberta-6l-768d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/tinyroberta-6l-768d with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="deepset/tinyroberta-6l-768d")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/tinyroberta-6l-768d") model = AutoModelForQuestionAnswering.from_pretrained("deepset/tinyroberta-6l-768d", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 105599a6dd626f3a542a2d3dbf677a57376b7a057f1e4574b8da97f8abce4adf
- Size of remote file:
- 326 MB
- SHA256:
- 37e01747606f25c2a754be7efba39446367eeebaa0e847165253808a5194ebfd
路
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