Instructions to use phospho-app/phospho-small-2502093 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use phospho-app/phospho-small-2502093 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="phospho-app/phospho-small-2502093")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("phospho-app/phospho-small-2502093") model = AutoModel.from_pretrained("phospho-app/phospho-small-2502093") - Notebooks
- Google Colab
- Kaggle
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
from setfit import SetFitModel
model = SetFitModel.from_pretrained("phospho-small-2502093")
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.
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