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:
- 62c706937452fc9e2c03b32eb4dd92da9ad8fcb25475d6249f574041dad8349e
- Size of remote file:
- 1.71 MB
- SHA256:
- 04838e427d22ed457e33f9dcb6ef46fc7df06458c0f1b43115f1cd204048e1e1
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