Instructions to use hf-tiny-model-private/tiny-random-ConvBertForQuestionAnswering 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-ConvBertForQuestionAnswering 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-ConvBertForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-ConvBertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-ConvBertForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe96cf94c1a5784431cb4a0f6ed97ce9f3e6b8db5de67dbd9bfa5ead5b668d8a
- Size of remote file:
- 5.48 MB
- SHA256:
- f23998ab51a9f2342dd6e59356bce61d47f6dd5dad8cad22f215519b1ec2874c
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