# Load model directly
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("phospho-app/MODEL_ID")
model = AutoModel.from_pretrained("phospho-app/MODEL_ID")Quick Links
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("MODEL_ID")
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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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="phospho-app/MODEL_ID")