# Generate News in Thai language by keywords.

MODEL_NAME = 'nonamenlp/news_gen' 

TOKENIZER_NAME = "nonamenlp/news_gen"

trained_model = MT5ForConditionalGeneration.from_pretrained(MODEL_NAME, return_dict=True)

tokenizer = T5Tokenizer.from_pretrained(TOKENIZER_NAME)
{}
transformers pytorch jax mt5 text2text-generation autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #jax #mt5 #text2text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

# Generate News in Thai language by keywords.

MODEL_NAME = 'nonamenlp/news_gen' 

TOKENIZER_NAME = "nonamenlp/news_gen"

trained_model = MT5ForConditionalGeneration.from_pretrained(MODEL_NAME, return_dict=True)

tokenizer = T5Tokenizer.from_pretrained(TOKENIZER_NAME)
# Generate News in Thai language by keywords.

MODEL_NAME = 'nonamenlp/news_gen' 

TOKENIZER_NAME = "nonamenlp/news_gen"

trained_model = MT5ForConditionalGeneration.from_pretrained(MODEL_NAME, return_dict=True)

tokenizer = T5Tokenizer.from_pretrained(TOKENIZER_NAME)
TAGS
#transformers #pytorch #jax #mt5 #text2text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # Generate News in Thai language by keywords.

MODEL_NAME = 'nonamenlp/news_gen' 

TOKENIZER_NAME = "nonamenlp/news_gen"

trained_model = MT5ForConditionalGeneration.from_pretrained(MODEL_NAME, return_dict=True)

tokenizer = T5Tokenizer.from_pretrained(TOKENIZER_NAME)
passage: TAGS
#transformers #pytorch #jax #mt5 #text2text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# Generate News in Thai language by keywords.

MODEL_NAME = 'nonamenlp/news_gen' 

TOKENIZER_NAME = "nonamenlp/news_gen"

trained_model = MT5ForConditionalGeneration.from_pretrained(MODEL_NAME, return_dict=True)

tokenizer = T5Tokenizer.from_pretrained(TOKENIZER_NAME)