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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