Instructions to use bigcode/santacoder-fast-inference with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bigcode/santacoder-fast-inference with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="bigcode/santacoder-fast-inference")# Load model directly from transformers import AutoTokenizer, AutoModelWithLMHead tokenizer = AutoTokenizer.from_pretrained("bigcode/santacoder-fast-inference") model = AutoModelWithLMHead.from_pretrained("bigcode/santacoder-fast-inference") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f66a274bc3eb18dc1882b0f4c60e2e681493d046e07d6f7467e271a0a6893001
- Size of remote file:
- 2.25 GB
- SHA256:
- 50d0abae8bfd19082f125e7a40567cba71de296637802eb70157fe55fa66923f
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