| --- |
| language: |
| - en |
| tags: |
| - recommendation |
| - multimodal |
| - sequential-recommendation |
| --- |
| |
| # MoSID preprocessed data |
|
|
| Preprocessed item features and sequence splits for the Movies dataset in nm mode. |
|
|
| ## Layout |
|
|
| The files under `Movies/nm/` use the same contiguous item IDs. ID 0 is reserved for padding; valid item IDs are 1 through N. |
|
|
| | File | Content | |
| | --- | --- | |
| | txt_emb.pt | Text embedding tensor, shape [N+1, 768] | |
| | img_emb.pt | Visual embedding tensor, shape [N+1, 768] | |
| | collab_emb.pt | Collaborative embedding tensor, shape [N+1, 256] | |
| | mod_presence.pt | Boolean tensor, shape [N+1, 2], for text and visual availability | |
| | mappings.pkl | Mapping dictionary containing item2id | |
| | train.pkl | Training item_seqs and labels | |
| | valid.pkl | Validation item_seqs and labels | |
| | test.pkl | Test item_seqs and labels | |
| |
| Place the `Movies` directory under `datasets/amazon/` in the MoSID source repository. Semantic IDs and codebook weights are generated by the Stage 1 training and export commands provided in the source repository. |
| |
| ## Integrity |
| |
| `SHA256SUMS.txt` contains the SHA-256 hashes of the released data files. |
| |
| ## Serialization |
| |
| The `.pt` files contain PyTorch tensors. The `.pkl` files use Python pickle. Only load serialized files from a trusted source. |
| |
