| from sentence_transformers import SentenceTransformer |
| from torch.nn import EmbeddingBag |
| import torch |
|
|
| model = SentenceTransformer("tomaarsen/static-retrieval-mrl-en-v1") |
| embedding_bag: EmbeddingBag = model[0].embedding |
| embeddings = torch.Tensor(embedding_bag.weight) |
|
|
| assert embeddings.shape == torch.Size([30522, 1024]) |
|
|
| print(f"1024 dim - {embeddings.shape[0] * 1024 * 4 / 1024 / 1024:,.1f} MiB:") |
| print(f"512 dim - {embeddings.shape[0] * 512 * 4 / 1024 / 1024:,.1f} MiB:") |
| print(f"256 dim - {embeddings.shape[0] * 256 * 4 / 1024 / 1024:,.1f} MiB:") |
|
|
| print("Embeddings[0]", embeddings[0]) |
|
|