Instructions to use hf-internal-testing/tiny-random-GPTJForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPTJForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-GPTJForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPTJForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-GPTJForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 639bb14bbb8d37a7d0c27cde6d91c3bba3c6d0b99bcffec4548ea5225e951b81
- Size of remote file:
- 469 kB
- SHA256:
- b46b83e76fb9cd0e69270744ec8411f1e670ad34a987d4da282f51b0e2749b6b
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