Instructions to use hf-internal-testing/tiny-random-OpenAIGPTModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-OpenAIGPTModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-OpenAIGPTModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-OpenAIGPTModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-OpenAIGPTModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d14e754fe6685718d74cb2b2630ec88607bb39b4b7cbd3a6b4868138cf05bbec
- Size of remote file:
- 582 kB
- SHA256:
- 8c9dae59a132e725bd9243920323570b6a0001efad47d4962db29e07cd4525ee
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