Instructions to use hf-tiny-model-private/tiny-random-IBertForQuestionAnswering 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-IBertForQuestionAnswering 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-IBertForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-IBertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-IBertForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c98041d55fa2b157e586bd16914fcb8b97b469a2371b0301fa76753dfd0274ea
- Size of remote file:
- 813 kB
- SHA256:
- 45de2943db90c035aac053ebfd3bc5845cb70653f6161b1dff17cb3975567279
路
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