Comments (3)
Unfortunately this is not possible at the moment. I agree it would be a useful feature to open source. Keep an eye on future releases 😉
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You can try this using constant initializer, to initialize your new model with old embeddings. you also need to ensure that model dictionary(model.ent_to_idx, model.rel_to_idx) stays the same with the new data.
However this is not same as continuing training, since the optimizer states wont be the same.
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Unfortunately this is not possible at the moment. I agree it would be a useful feature to open source. Keep an eye on future releases 😉
@lukostaz does this mean we have to retrain the model from start if we want to add new triplets? What do you suggest for adding a KG in production that needs to be updated frequently? Thanks.
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Related Issues (20)
- A spelling mistake in `ampligraph/latent_features/models/EmbeddingModel.py` or documentation causes the training model different the documentation's
- Predict Head or Tail candidates using GraphSAGE model
- 'ConvKB' object has no attribute 'corr_batch_size' HOT 1
- load_from_ntriples() doesn't work as expected HOT 1
- Migrate to tensor flow 2 HOT 5
- https://github.com/Accenture/AmpliGraph/blob/d4bf44559cb7178039f21203780be4eb946ea4eb/experiments/IJCAI-21/experiments.py#L12 HOT 1
- ConvE has no attribute tensorboard_logs_path
- generate_candidates() doesn't work as expected - generates same triplet
- Implement NodePieces HOT 1
- FocusE-ComplEx: Question on using numeric edge weight attributes - prediction performance (MRR) and embeddings are very similar between models with and without edge weights
- discovery.py library, discover_facts function, when returning np.hstack if some array is empty
- Can we pass custom trained embedding as entity and then train the model?
- Multiple GPU for training
- AttributeEerro while running the code HOT 1
- ImportError: cannot import name 'ConvKB' from 'ampligraph.latent_features' HOT 3
- Train and Test Data split error HOT 2
- Ampligraph Embedding for Protein Sequences
- AttributeError: 'ScoringBasedEmbeddingModel' object has no attribute '_reset_compile_cache' HOT 2
- AttributeError: 'ScoringBasedEmbeddingModel' object has no attribute '_reset_compile_cache'
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