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:
- fd8f454a9be424bb92e69245c55ddfa2252e04995cbd2698ea46661a6707026f
- Size of remote file:
- 320 kB
- SHA256:
- 8676ceb74d9d4a8551c050de802bd322b4db93bc57bfc387308d2974f54abb2a
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