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:
- c27fb91a056ebbd99af2524fcd6d7f8a5f150f9f64cedd389bc406836a97bc48
- Size of remote file:
- 1.71 MB
- SHA256:
- 3eb5301ec9c7b21ffb9eb2421ece096adf8df1bda60d275097b58b3a8307b69f
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