Instructions to use erickdp/ssa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use erickdp/ssa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="erickdp/ssa")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("erickdp/ssa") model = AutoModelForSequenceClassification.from_pretrained("erickdp/ssa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 21012320df8373814ab2f1cf2aecb7f2c788cc783c5d85efa3209c3db5d189e5
- Size of remote file:
- 4.86 kB
- SHA256:
- 6553612e355c002634d49da205fed648687fb06e2c9467bc9a3af0b687bfc1d9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.