Instructions to use hf-tiny-model-private/tiny-random-DistilBertForQuestionAnswering 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-DistilBertForQuestionAnswering 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-DistilBertForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-DistilBertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-DistilBertForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff886ece7aa21993f15dd4ea3dee281f86c9b79af64be875b570909a128b942a
- Size of remote file:
- 456 kB
- SHA256:
- aa1a72bf2734fbaf105d5786685afc0729f0e419057fc2a225540e9fdf5fbce4
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