belgpt2

比利时 GPT-2 ??

在非常大且异构的法语语料库 (~60Gb) 上预训练的 GPT-2 模型。

用法

您可以将 BelGPT-2 与 ? Transformer库如下：

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)">

 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 )

文档

有关预训练模型、其实现和数据的详细文档可以在此处找到。

引文

对于学术背景下的归属，请将本作品引用为：

belgpt2, author = {Louis, Antoine}, title = {{BelGPT-2: a GPT-2 model pre-trained on French corpora.}}, year = {2020}, howpublished = {url{https://github.com/antoiloui/belgpt2}}, }">

 @misc{louis2020 belgpt2 ,
  author = {Louis, Antoine},
  title = {{BelGPT-2: a GPT-2 model pre-trained on French corpora.}},
  year = {2020},
  howpublished = {url{https://github.com/antoiloui/belgpt2}},
}