Instructions to use hf-internal-testing/tiny-random-DPRQuestionEncoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DPRQuestionEncoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-DPRQuestionEncoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-DPRQuestionEncoder") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-DPRQuestionEncoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12ab34a0e8e06985ca2e550dc4e9b92bb4e97d9650125f67fa48f559a1fdc550
- Size of remote file:
- 471 kB
- SHA256:
- 0a0a5ee0699284cd4ca3095bcc58a6546162e855af0d09c3378f94567ffd3495
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