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This model uses the Llama-3 model ("meta-llama/Meta-Llama-3-8B") fine-tuned with 4 bit quantization Parameter Efficient Fine Tuning - PEFT training, using LoRA and QLoRA adaptations for the task of Humor Recognition in Greek language.

Model Details

The model was pre-trained on Greek Humorous Dataset

PEFT Configs

  • Bits and bytes config for quantization - QLoRA
  • LoRA config for LoRA adaptation

Pre-processing details

The text needs to be pre-processed by:

  • removing all greek diacritics and punctuations
  • converting all letters to lowercase

Load Pretrained Model

pad_token needs to be handle since Llama-3 pre-training doesn't have eos_token

from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("kallantis/Humor-Recognition-Greek-Llama-3", add_prefix_space=True)

tokenizer.pad_token_id = tokenizer.eos_token_id
tokenizer.pad_token = tokenizer.eos_token

model = AutoModelForSequenceClassification.from_pretrained(
    "kallantis/Humor-Recognition-Greek-Llama-3",
    quantization_config=quantization_config,
    num_labels=2
)
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Dataset used to train kallantis/Humor-Recognition-Greek-Llama-3