Comments (6)
lukostaz
commented on June 5, 2024
All datasets uploaded to S3. Use the following:
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lukostaz
commented on June 5, 2024
Also added:
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rorymcgrath
commented on June 5, 2024
freebase13 'dev.txt' file needs to be renamed to 'valid.txt'
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lukostaz
commented on June 5, 2024
better not modify the original datasets (reproducibility, etc etc.)
This should be handled within the loader.
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rorymcgrath
commented on June 5, 2024
wordnet11 'dev.txt' file needs to be renamed to 'valid.txt'
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lukostaz
commented on June 5, 2024
We can move this to 1.1 (i.e. keep WN18 and FB13 loaders stuff in a branch, and remove them from the integration branch).
Neither dataset is used in these experiments, anyway.
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Related Issues (20)
- ValueError: `generator` yielded an element of shape (3,) where an element of shape (?, 3) was expected. HOT 1
- Is query_topn computes as same as evaluate_performance HOT 1
- 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
- Refit a trained model with new triplets HOT 3
- 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
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