Instructions to use hf-tiny-model-private/tiny-random-CodeGenModel 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-CodeGenModel 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-CodeGenModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-CodeGenModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-CodeGenModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 412a7d55409a57c25c4d0d167bcac4232df9b621381b841fd8572c32c2cb49c5
- Size of remote file:
- 1.7 MB
- SHA256:
- 062d3ee00203cf48f017453c9f02214ea8f96328f8fe27fd02313ab0ae1c4ba3
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