Wals — Roberta Sets Upd

import tensorflow as tf
import tensorflow_recommenders as tfrs
RoBERTa (Robustly Optimized BERT Approach) is a transformer-based language model pretrained on massive text corpora. In this setup, RoBERTa is not used for sequence generation but as an item encoder:

Would you like a full end-to-end Python script for applying WALS to RoBERTa on a custom dataset? wals roberta sets upd
Build a collaborative filtering model (WALS) where item representations are initially derived from RoBERTa embeddings of text descriptions. Would you like a full end-to-end Python script
For truly dynamic updates (e.g., news recommender), you cannot refit WALS fully or full RoBERTa fine-tune every minute. Instead: from peft import LoraConfig

from peft import LoraConfig, get_peft_model
lora_config = LoraConfig(r=8, lora_alpha=32, target_modules=["query", "value"])
roberta_lora = get_peft_model(roberta_model, lora_config)