Instructions to use hf-internal-testing/tiny-random-GPTBigCodeModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPTBigCodeModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-GPTBigCodeModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPTBigCodeModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-GPTBigCodeModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a52c09d579a7b13ad240306edbdfe23d24bc90b3ce56b19500169097d340b8cc
- Size of remote file:
- 306 kB
- SHA256:
- 31ca3fa1c325678e01efa18c6db21566fa36c26fbec4274cb74b92b4d8b6aee5
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