Instructions to use hf-tiny-model-private/tiny-random-BloomForQuestionAnswering 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-BloomForQuestionAnswering 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-BloomForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-BloomForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-BloomForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b68aa8936f88d00a6a30982002dce986e8e700328c80ffd0679aea1a6d642b8
- Size of remote file:
- 393 kB
- SHA256:
- 4148c7a23c87c1775f5f39bf5ecf31ec66e0955fc9aa7beef5dccdd6efc34c1b
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