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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e9368e6329d69a344e3c1c00cd979629aed51c26501970d308374ced045dbdc
- Size of remote file:
- 320 kB
- SHA256:
- 25c362907f2eb3c956b4089b6f42fe39a2777ccabaa18df4863e922d17f7d59b
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