---
library_name: transformers
license: apache-2.0
datasets:
- kallantis/Greek-Humorous-Dataset
language:
- el
pipeline_tag: text-classification
---
#
#
# 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

```python
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
)

```