How to use lewtun/my-awesome-setfit-model-98 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lewtun/my-awesome-setfit-model-98") 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 lewtun/my-awesome-setfit-model-98 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("lewtun/my-awesome-setfit-model-98")
How to use lewtun/my-awesome-setfit-model-98 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lewtun/my-awesome-setfit-model-98")
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("lewtun/my-awesome-setfit-model-98") model = AutoModel.from_pretrained("lewtun/my-awesome-setfit-model-98", device_map="auto")
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