metadata

license: apache-2.0
datasets:
  - mrm8488/CHISTES_spanish_jokes
language:
  - es
pipeline_tag: text-generation

TEST LORA

Adapter for BERTIN-GPT-J-6B fine-tuned on Jokes for jokes generation

Adapter Description

This adapter was created by using the PEFT library and allows the base model BERTIN-GPT-J-6B to be fine-tuned on the dataset mrm8488/CHISTES_spanish_jokes for Spanish jokes generation by using the method LoRA.

Model Description

BERTIN-GPT-J-6B is a Spanish finetuned version of GPT-J 6B, a transformer model trained using Ben Wang's Mesh Transformer JAX. "GPT-J" refers to the class of model, while "6B" represents the number of trainable parameters.

Training data

Dataset from Workshop for NLP introduction with Spanish jokes

More Information needed

Training procedure

TBA

How to use

import torch
from peft import PeftModel, PeftConfig
from transformers import AutoModelForCausalLM, AutoTokenizer

peft_model_id = "mrm8488/bertin-gpt-j-6B-es-finetuned-chistes_spanish_jokes-500"
config = PeftConfig.from_pretrained(peft_model_id)
model = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path, return_dict=True, load_in_8bit=True, device_map='auto')
tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)

# Load the Lora model
model = PeftModel.from_pretrained(model, peft_model_id)

# Inference
batch = tokenizer("Esto son dos amigos", return_tensors='pt')

with torch.cuda.amp.autocast():
  output_tokens = model.generate(**batch, max_new_tokens=50)

print('\n\n', tokenizer.decode(output_tokens[0], skip_special_tokens=True))