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:
- e4fc1f24319257cfa4770cda075f3e11f51ed41b7053bcaf69dbbe4f25c08704
- Size of remote file:
- 326 MB
- SHA256:
- 3fd7a0c8706549570e1a5af2f11b2661e8d8987a96b40649a4311303e9490148
路
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