Text Retrieval
Transformers
PyTorch
English
t5
recommendation
sequential-recommendation
text-generation-inference
Instructions to use xhd0728/LISRec-MFilter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xhd0728/LISRec-MFilter with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("xhd0728/LISRec-MFilter") model = AutoModel.from_pretrained("xhd0728/LISRec-MFilter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 67a64e767bddfe0723ec83409772e49bf222697ea5224163a5d378fcce8bd318
- Size of remote file:
- 1.78 GB
- SHA256:
- 3ce33a37c1ff366384dfbc1b6726afcb2ec5b5c7931125889066f68a3458d0a1
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