Instructions to use hf-tiny-model-private/tiny-random-RoFormerForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-RoFormerForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-tiny-model-private/tiny-random-RoFormerForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RoFormerForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-RoFormerForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c747b2613438fd5983cde8ff7328356ccc04ab5195088cff0f3378ad6588229
- Size of remote file:
- 6.68 MB
- SHA256:
- 36840f828a2e8dde157f72ae6b5a9679b5700393fbb37904a3e8a212e3b1812d
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