Instructions to use hf-internal-testing/tiny-random-GPTJModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPTJModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-GPTJModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPTJModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-GPTJModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f789020e1b2f9cdd7c3c8b21537a04904a68dfe425252fea5daf1cd696893a46
- Size of remote file:
- 460 kB
- SHA256:
- 3d97001d919d051c2279448277096c338d79f1eee5a54c5e213bfedf86b902bd
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