Instructions to use Ericwang/tiny-random-ast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ericwang/tiny-random-ast with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Ericwang/tiny-random-ast")# Load model directly from transformers import AutoFeatureExtractor, AutoModel extractor = AutoFeatureExtractor.from_pretrained("Ericwang/tiny-random-ast") model = AutoModel.from_pretrained("Ericwang/tiny-random-ast") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8bfe5d29298900311e920d377d657d00faaba0fa16b0eccfdb50120bbf5ad098
- Size of remote file:
- 336 kB
- SHA256:
- a58a3b79659b51e9f958d64b2771fdadb7edc1c21bb01f55a47bce16b867573c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.