sentence-transformers How to use Syldehayem/all-MiniLM-L12-v2_embedder_train with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("Syldehayem/all-MiniLM-L12-v2_embedder_train")
sentences = [
"CGI 3D Animated Short \"The Scarf\" - by Team The Scarf",
"CGI 3D Short: \"Lenovo Legion: Turning Point\" - by Audis Huang & Moonshine Animation | TheCGBros",
"CGI Animated Trailers : \"Dropzone\" - by RealtimeUK",
"CGI 3D Animated Short: \"SOLVIVAL\" - by Pixelhunters | TheCGBros"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
