Comments (2)
rnyak
commented on June 15, 2024
@ralgond NVTabular is easy to use. you can take our existing notebooks and just add your data in it.
if you want to use pandas sure, go for it. but then you need to use schema file yourself manually and correctly, so that you can train a TF4Rec model. Please note that NVTabular generates schema file automatically.
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ralgond
commented on June 15, 2024
ok, thank you, I would try to learn NVTabular.
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Related Issues (20)
- [QST] error related to schema HOT 2
- Users' Long term and short term interests HOT 7
- [QST] RuntimeError: Error: <class 'AttributeError'> - 'list_iterator' object has no attribute 'names' HOT 4
- [QST] Visualize the NN architecture HOT 2
- [QST] How to extract hidden state and viz attention layers HOT 3
- [QST] how does the sequence data (3d tensor) ==> MLP block?
- set schema for movielens dataset HOT 7
- Evaluation is incorrect because it can see the label. [BUG] HOT 1
- PicklingError HOT 7
- [QST] Custom dataset with interacion only HOT 4
- [BUG] 'Trainer' object has no attribute '_pad_across_processes' HOT 7
- [BUG] conda env import error cudf HOT 2
- [FEA] Feature to extract attention values from transformer heads
- [BUG] Incorrect scores for evaluation
- [FEA] Multi-task prediction support with Next-Item-Prediction HOT 1
- [QST] ValueError: For masking a categorical_module is required including an item_id.
- [QST] Projecting inputs of NextItemPredictionTask to'64' As weight tying requires the input dimension '320' to be equal to the item-id embedding dimension '64' HOT 4
- [QST] Cross-entropy and pairwise losses are supported in Next Item Prediction
- [QST] How to print metrics while training?
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