- Added a `PreembeddingEmbedder` for embedding single-sequence (NUM_RESIDUE, ...) shaped embeddings as input.

- Added configuration options in `config.py` for toggling seq-emb mode
- Added list for specifying features to be used in seq-emb mode.

- New method for generating dummy MSA features.

…f MSAs.

- Added a `seq_emb` bool flag to `data_pipeline > process_fasta()`
- In `seqemb_mode` use dummy MSA features instead of full ones.

…b mode.

- Added a method to load and process sequence embedding `*.pt` files.
- In `seqemb_mode`, now add seqemb features to the feature dictionary.

…processors.

- Added `use_single_seq_mode` flag in inference script arguments.
- Passed on the flag to the FASTA file `data_processor`.

…del in `seqemb` mode.

- `seqemb_mode_enabled` added as a configuration option.
- `model.py` switches to using the `PreembeddingEmbedder` when the flag is `True`.

- Added `preembedding_embedder` config dictionary in `config`
- Added `preemb_dim_size` property in `config` for specifying single seq embedding size.

…nce embeddings.

- Added flag `no_column_attention` in evoformer config.
- Added check in `evoformer.py` to switch off `MSAColumnAttention` when the config flag `no_column_attention` is `True`.

…ddings when in `seqemb` mode.

- Use sequence embedding files when in `seqemb` mode.
- Make dummy MSA features for MMCIF when using `seqemb` mode.

…`data_pipeline` for training and inference pipelines.

- Passing the config.data.seqemb_mode.enabled flag to the FASTA, PDB, and MMCIF data pipelines.

- Turn on `seqemb` mode in `data`, `model`, and `globals` config when using `seqemb` training preset.

- Turn on `seqemb` mode in `data`, `model`, and `globals` config when using `seqemb` training preset.
- Set configuration options specific for finetuning in general.

- Bugfix: `torch` throws warnings when copying a tensor via initialization
- Added lambda to `.clone()` those tensors instead

…seqemb feature dictionary.

- `_process_seqemb_features` now returns a dictionary instead of a tensor.

… feature pipeline , if using seq_emb mode

- In `seq_emb` mode, add list of `seq_emb` features to `feature_names`

- In `seq_emb` mode, the AlignmentRunner works only on generating templates.

- In `seqemb_mode`, `process_pdb` loads sequence embedding for the PDB's protein, and a dummy MSA

… mask if there is only input sequence in MSA.

- Set `max_msa_clusters=1` in model presets for allowing the input sequence to be a MSA cluster centre.