File size: 788 Bytes
8e34a0b 226d5e5 8e34a0b 226d5e5 8e34a0b 226d5e5 8e34a0b 226d5e5 8e34a0b 226d5e5 8e34a0b 226d5e5 8e34a0b 226d5e5 8e34a0b 226d5e5 8e34a0b 226d5e5 8e34a0b 226d5e5 8e34a0b 226d5e5 8e34a0b 226d5e5 8e34a0b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 |
---
language: en
license: apache-2.0
---
# phospho-small
This is a SetFit model that can be used for Text Classification on CPU.
The model has been trained using an efficient few-shot learning technique.
## Usage
```python
from setfit import SetFitModel
model = SetFitModel.from_pretrained("phospho-small-46f5c4e")
outputs = model.predict(["This is a sentence to classify", "Another sentence"])
# tensor([1, 0])
```
## References
This work was possible thanks to the SetFit library and the work of:
Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren (2022). Efficient Few-Shot Learning Without Prompts.
ArXiv: [https://doi.org/10.48550/arxiv.2209.11055](https://doi.org/10.48550/arxiv.2209.11055)
|