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:
- dc5a297b5b6968f209637d2ba23c633c96d66003a08b5f3ca095ae5f0bbca352
- Size of remote file:
- 320 kB
- SHA256:
- f81c1a061cd608eeab9e63fdbb37bfd4be778386ba97d712ddd080c734b75563
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