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:
- 69544239fdc4bf21b3665e67596cb832f028f0c67e4fe56cfae1866d51e1b151
- Size of remote file:
- 320 kB
- SHA256:
- 1da0321fe24cdd099dc3b0fbd608d5cdb7fbba1f458053afefad25c828ccf12c
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