inference:
  parameters:
    max_length: 120
    do_sample: true
    temperature: 0.8

# GPT-2

Pretrained gpt model on Vietnamese New for text summarization

# How to use the model

~~~~
from transformers import GPT2Tokenizer, GPT2LMHeadModel

tokenizer = GPT2Tokenizer.from_pretrained('minhtoan/gpt2-finetune-vietnamese-news')
model = GPT2LMHeadModel.from_pretrained('minhtoan/gpt2-finetune-vietnamese-news')

text = "Hoa quả và rau thường rẻ hơn khi vào mùa"
input_ids = tokenizer.encode(text, return_tensors='pt')
max_length = 80

sample_outputs = model.generate(input_ids,pad_token_id=tokenizer.eos_token_id,
                                   do_sample=True,
                                   max_length=max_length,
                                   min_length=max_length,
                                   num_return_sequences=3)

for i, sample_output in enumerate(sample_outputs):
    print(">> Generated text {}\n\n{}".format(i+1, tokenizer.decode(sample_output.tolist())))
    print('\n---')
~~~~


## Author
`
Phan Minh Toan 
`
{"language": "vi", "tags": ["vi", "vietnamese", "gpt2", "text-generation", "lm", "nlp"], "datasets": ["vietnews"], "widget": [{"text": "T\u00f3m t\u1eaft v\u0103n b\u1ea3n: Hoa qu\u1ea3 v\u00e0 rau th\u01b0\u1eddng r\u1ebb h\u01a1n khi v\u00e0o m\u00f9a. K\u1ebft qu\u1ea3 t\u00f3m t\u1eaft v\u0103n b\u1ea3n l\u00e0:"}]}
transformers pytorch gpt2 text-generation vi vietnamese lm nlp dataset:vietnews autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #gpt2 #text-generation #vi #vietnamese #lm #nlp #dataset-vietnews #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

inference:
  parameters:
    max_length: 120
    do_sample: true
    temperature: 0.8

# GPT-2

Pretrained gpt model on Vietnamese New for text summarization

# How to use the model

~~~~
from transformers import GPT2Tokenizer, GPT2LMHeadModel

tokenizer = GPT2Tokenizer.from_pretrained('minhtoan/gpt2-finetune-vietnamese-news')
model = GPT2LMHeadModel.from_pretrained('minhtoan/gpt2-finetune-vietnamese-news')

text = "Hoa quả và rau thường rẻ hơn khi vào mùa"
input_ids = URL(text, return_tensors='pt')
max_length = 80

sample_outputs = model.generate(input_ids,pad_token_id=tokenizer.eos_token_id,
                                   do_sample=True,
                                   max_length=max_length,
                                   min_length=max_length,
                                   num_return_sequences=3)

for i, sample_output in enumerate(sample_outputs):
    print(">> Generated text {}\n\n{}".format(i+1, URL(sample_output.tolist())))
    print('\n---')
~~~~


## Author
'
Phan Minh Toan 
'
# GPT-2

Pretrained gpt model on Vietnamese New for text summarization # How to use the model

~~~~
from transformers import GPT2Tokenizer, GPT2LMHeadModel

tokenizer = GPT2Tokenizer.from_pretrained('minhtoan/gpt2-finetune-vietnamese-news')
model = GPT2LMHeadModel.from_pretrained('minhtoan/gpt2-finetune-vietnamese-news')

text = "Hoa quả và rau thường rẻ hơn khi vào mùa"
input_ids = URL(text, return_tensors='pt')
max_length = 80

sample_outputs = model.generate(input_ids,pad_token_id=tokenizer.eos_token_id,
                                   do_sample=True,
                                   max_length=max_length,
                                   min_length=max_length,
                                   num_return_sequences=3)

for i, sample_output in enumerate(sample_outputs):
    print(">> Generated text {}\n\n{}".format(i+1, URL(sample_output.tolist())))
    print('\n---')
~~~~ ## Author
'
Phan Minh Toan 
'
TAGS
#transformers #pytorch #gpt2 #text-generation #vi #vietnamese #lm #nlp #dataset-vietnews #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # GPT-2

Pretrained gpt model on Vietnamese New for text summarization # How to use the model

~~~~
from transformers import GPT2Tokenizer, GPT2LMHeadModel

tokenizer = GPT2Tokenizer.from_pretrained('minhtoan/gpt2-finetune-vietnamese-news')
model = GPT2LMHeadModel.from_pretrained('minhtoan/gpt2-finetune-vietnamese-news')

text = "Hoa quả và rau thường rẻ hơn khi vào mùa"
input_ids = URL(text, return_tensors='pt')
max_length = 80

sample_outputs = model.generate(input_ids,pad_token_id=tokenizer.eos_token_id,
                                   do_sample=True,
                                   max_length=max_length,
                                   min_length=max_length,
                                   num_return_sequences=3)

for i, sample_output in enumerate(sample_outputs):
    print(">> Generated text {}\n\n{}".format(i+1, URL(sample_output.tolist())))
    print('\n---')
~~~~ ## Author
'
Phan Minh Toan 
'
TAGS
#transformers #pytorch #gpt2 #text-generation #vi #vietnamese #lm #nlp #dataset-vietnews #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# GPT-2

Pretrained gpt model on Vietnamese New for text summarization# How to use the model

~~~~
from transformers import GPT2Tokenizer, GPT2LMHeadModel

tokenizer = GPT2Tokenizer.from_pretrained('minhtoan/gpt2-finetune-vietnamese-news')
model = GPT2LMHeadModel.from_pretrained('minhtoan/gpt2-finetune-vietnamese-news')

text = "Hoa quả và rau thường rẻ hơn khi vào mùa"
input_ids = URL(text, return_tensors='pt')
max_length = 80

sample_outputs = model.generate(input_ids,pad_token_id=tokenizer.eos_token_id,
                                   do_sample=True,
                                   max_length=max_length,
                                   min_length=max_length,
                                   num_return_sequences=3)

for i, sample_output in enumerate(sample_outputs):
    print(">> Generated text {}\n\n{}".format(i+1, URL(sample_output.tolist())))
    print('\n---')
~~~~## Author
'
Phan Minh Toan 
'