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")# 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:
- f10c4f995675ff5e35d712ae576e9967dc8f691081d5a94b7605f9252a032fbd
- Size of remote file:
- 469 kB
- SHA256:
- dd6595245b4ee90c4bee6ce20b95f4886c4f66d78ce34ae129aaf9d6b531b689
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