Instructions to use hf-tiny-model-private/tiny-random-FlaubertForQuestionAnsweringSimple 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-FlaubertForQuestionAnsweringSimple 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-FlaubertForQuestionAnsweringSimple")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FlaubertForQuestionAnsweringSimple") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-FlaubertForQuestionAnsweringSimple") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b53681f96ca3a7f12b3a5bd9b35ed0aa8c5f2fd66f3ef5a7affe6cadd29033d4
- Size of remote file:
- 8.97 MB
- SHA256:
- dda064c2c582f9d5218499caf2f7820de31538eeec9f93cbfd6eeb9ff929b77e
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