How to use vgarg/my_zs_model2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("vgarg/my_zs_model2") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3]
How to use vgarg/my_zs_model2 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("vgarg/my_zs_model2") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds)
https://huggingface.co/vgarg/my_zs_model2/resolve/main/tokenizer.json
hf download hf://vgarg/my_zs_model2/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/vgarg/my_zs_model2/resolve/main/tokenizer.json
