NVIDIA-Merlin / NVIDIA-Merlin/Transformers4Rec
Dual Transformer for long term and short term seq[QST]
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- Dominant language
- Python
- Stars
- 1.3k
- Forks
- 165
- Avg merge
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- Merged PRs (30d)
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Description
❓ Questions & Help
Details
Im working on a project that requires me to produce a stable long-term user and item representation and also use short-term user behavior for next action prediction. Is it possible to create a custom architecture to train two transformer towers together with different inputs and then have concat at later point. What is the recommended architecture for problems like this.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No file, test, or entry point is identified, and the issue asks for architectural guidance rather than a defined change. Start by reviewing the repository's existing transformer and recommendation components, then clarify the two input representations, training objective, and expected concatenation behavior; done would be a maintainer-approved architecture or a separately scoped implementation issue.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100