Instructions to use hf-tiny-model-private/tiny-random-GPTJModel 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-GPTJModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-GPTJModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-GPTJModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-GPTJModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a1796d66bcee8f841f9727dd695c8e33bfc49244c223479ccbb39627774837b2
- Size of remote file:
- 1.71 MB
- SHA256:
- 4e3848f184b515175219a29ea88955b3ef197e8766f162d2b428780852672b55
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