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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 92f52b5118ae138a583d7bca16ccc7788864baadea7edfd450d1ff29505969ce
- Size of remote file:
- 9.07 MB
- SHA256:
- cc19cfcea70bc47ffa83087c710e1e3d2dfeaff61fbd5fd01baf32706edac275
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