Instructions to use hf-tiny-model-private/tiny-random-YosoForQuestionAnswering 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-YosoForQuestionAnswering 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-YosoForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-YosoForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-YosoForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5fc9260aeae0630a24d61009a5b3063028c3734f5ccd96b2c5e0bc953fdf46f1
- Size of remote file:
- 349 kB
- SHA256:
- cf45da7f6229e8181971ff424ef56e95ba431b4d8f399c064c4ce7113ec75abb
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