A GPT-2 model pre-trained on a very large and heterogeneous French corpus (~60Gb).
You can use BelGPT-2 with 🤗 Transformers library as follows:
import torch
from transformers import GPT2Tokenizer, GPT2LMHeadModel
# Load pretrained model and tokenizer
model = GPT2LMHeadModel.from_pretrained("antoiloui/belgpt2")
tokenizer = GPT2Tokenizer.from_pretrained("antoiloui/belgpt2")
# Generate a sample of text
model.eval()
output = model.generate(
bos_token_id=random.randint(1,50000),
do_sample=True,
top_k=50,
max_length=100,
top_p=0.95,
num_return_sequences=1
)
# Decode it
decoded_output = []
for sample in output:
decoded_output.append(tokenizer.decode(sample, skip_special_tokens=True))
print(decoded_output)Detailed documentation on the pre-trained model, its implementation, and the data can be found here.
For attribution in academic contexts, please cite this work as:
@misc{louis2020belgpt2,
author = {Louis, Antoine},
title = {{BelGPT-2: a GPT-2 model pre-trained on French corpora.}},
year = {2020},
howpublished = {\url{https://github.com/antoiloui/belgpt2}},
}
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