Instructions to use hf-tiny-model-private/tiny-random-GPTJForQuestionAnswering 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-GPTJForQuestionAnswering 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-GPTJForQuestionAnswering", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-GPTJForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-GPTJForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c95d117694efbece02d7732edd708d049a46686ba5c411c566545f07b00044c
- Size of remote file:
- 1.7 MB
- SHA256:
- 72f6370749705124de21e4c66f254cec97e226e5971be6b274d3741660f7b7d8
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