hlt_usppm's Introduction
hlt_usppm's People
hlt_usppm's Issues
Grid search con fine tuning
Prompt learning con prompt discreti
Grid search senza fine tuning
cose da leggere
- Toutorial on sematic similarity evaluation with transformers https://towardsdatascience.com/bert-for-measuring-text-similarity-eec91c6bf9e1
https://github.com/jamescalam/transformers/blob/main/course/similarity/03_calculating_similarity.ipynb - Adversarial training (Fast Gradient Method -> https://www.kaggle.com/competitions/tweet-sentiment-extraction/discussion/143764)
- Prompt-based Learning (https://blog.paperspace.com/prompt-based-learning-in-natural-language-processing/) (https://thegradient.pub/prompting/)
- Notebook abbastanza semplice e lineare per capire un po' come lavorare https://www.kaggle.com/code/yudelune6101068/pppm-deberta-v3-large-baseline-inference
- Keras NLP https://keras.io/guides/keras_nlp/transformer_pretraining/
- Keras semantic similarity https://keras.io/examples/nlp/semantic_similarity_with_bert/
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