Instructions to use hf-tiny-model-private/tiny-random-RemBertForQuestionAnswering 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-RemBertForQuestionAnswering 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-RemBertForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RemBertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-RemBertForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8948bc6a288c12192dae35137a5467d774a344e0e21912104978cb955aed376e
- Size of remote file:
- 18.3 MB
- SHA256:
- 1e8eabe42e6edb3b0806b2373d2fafc14b2c6ad77c4c7e9e1ad0a91a3026ea5b
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