How to use LeoCristt/hackathon-embedding-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("LeoCristt/hackathon-embedding-model") 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 LeoCristt/hackathon-embedding-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="LeoCristt/hackathon-embedding-model", device_map="auto")
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("LeoCristt/hackathon-embedding-model") model = AutoModel.from_pretrained("LeoCristt/hackathon-embedding-model", device_map="auto")
