
# GPT-3 small

Pretrained GPT-3 small, continuing the development of GPT NEO, with architecture that purposefully mimics that of GPT-3, model was trained on CNN Daily Mail News dataset for text generation.
# How to use the model

~~~~
from transformers import GPT2Tokenizer, GPTNeoForCausalLM

tokenizer = GPT2Tokenizer.from_pretrained('minhtoan/gpt3-small-finetune-cnndaily-news')
model = GPTNeoForCausalLM.from_pretrained('minhtoan/gpt3-small-finetune-cnndaily-news')

text = "Ever noticed how plane seats appear to be getting smaller and smaller? "
input_ids = tokenizer.encode(text, return_tensors='pt')
max_length = 150

sample_outputs = model.generate(input_ids, do_sample=True, max_length=max_length,temperature = 0.8)

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": ["en"], "tags": ["en", "english", "gpt2", "gpt3", "text-generation", "lm", "nlp"], "datasets": ["cnn_dailymail"], "widget": [{"text": "Ever noticed how plane seats appear to be getting smaller and smaller? "}], "inference": {"parameters": {"max_length": 120, "do_sample": true, "temperature": 0.8}}}
transformers pytorch gpt_neo text-generation en english gpt2 gpt3 lm nlp dataset:cnn_dailymail autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #gpt_neo #text-generation #en #english #gpt2 #gpt3 #lm #nlp #dataset-cnn_dailymail #autotrain_compatible #endpoints_compatible #region-us 


# GPT-3 small

Pretrained GPT-3 small, continuing the development of GPT NEO, with architecture that purposefully mimics that of GPT-3, model was trained on CNN Daily Mail News dataset for text generation.
# How to use the model

~~~~
from transformers import GPT2Tokenizer, GPTNeoForCausalLM

tokenizer = GPT2Tokenizer.from_pretrained('minhtoan/gpt3-small-finetune-cnndaily-news')
model = GPTNeoForCausalLM.from_pretrained('minhtoan/gpt3-small-finetune-cnndaily-news')

text = "Ever noticed how plane seats appear to be getting smaller and smaller? "
input_ids = URL(text, return_tensors='pt')
max_length = 150

sample_outputs = model.generate(input_ids, do_sample=True, max_length=max_length,temperature = 0.8)

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-3 small

Pretrained GPT-3 small, continuing the development of GPT NEO, with architecture that purposefully mimics that of GPT-3, model was trained on CNN Daily Mail News dataset for text generation. # How to use the model

~~~~
from transformers import GPT2Tokenizer, GPTNeoForCausalLM

tokenizer = GPT2Tokenizer.from_pretrained('minhtoan/gpt3-small-finetune-cnndaily-news')
model = GPTNeoForCausalLM.from_pretrained('minhtoan/gpt3-small-finetune-cnndaily-news')

text = "Ever noticed how plane seats appear to be getting smaller and smaller? "
input_ids = URL(text, return_tensors='pt')
max_length = 150

sample_outputs = model.generate(input_ids, do_sample=True, max_length=max_length,temperature = 0.8)

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 #gpt_neo #text-generation #en #english #gpt2 #gpt3 #lm #nlp #dataset-cnn_dailymail #autotrain_compatible #endpoints_compatible #region-us 
 # GPT-3 small

Pretrained GPT-3 small, continuing the development of GPT NEO, with architecture that purposefully mimics that of GPT-3, model was trained on CNN Daily Mail News dataset for text generation. # How to use the model

~~~~
from transformers import GPT2Tokenizer, GPTNeoForCausalLM

tokenizer = GPT2Tokenizer.from_pretrained('minhtoan/gpt3-small-finetune-cnndaily-news')
model = GPTNeoForCausalLM.from_pretrained('minhtoan/gpt3-small-finetune-cnndaily-news')

text = "Ever noticed how plane seats appear to be getting smaller and smaller? "
input_ids = URL(text, return_tensors='pt')
max_length = 150

sample_outputs = model.generate(input_ids, do_sample=True, max_length=max_length,temperature = 0.8)

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 #gpt_neo #text-generation #en #english #gpt2 #gpt3 #lm #nlp #dataset-cnn_dailymail #autotrain_compatible #endpoints_compatible #region-us 
# GPT-3 small

Pretrained GPT-3 small, continuing the development of GPT NEO, with architecture that purposefully mimics that of GPT-3, model was trained on CNN Daily Mail News dataset for text generation.# How to use the model

~~~~
from transformers import GPT2Tokenizer, GPTNeoForCausalLM

tokenizer = GPT2Tokenizer.from_pretrained('minhtoan/gpt3-small-finetune-cnndaily-news')
model = GPTNeoForCausalLM.from_pretrained('minhtoan/gpt3-small-finetune-cnndaily-news')

text = "Ever noticed how plane seats appear to be getting smaller and smaller? "
input_ids = URL(text, return_tensors='pt')
max_length = 150

sample_outputs = model.generate(input_ids, do_sample=True, max_length=max_length,temperature = 0.8)

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 
'