mesolitica
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t5-super-tiny-standard-bahasa-cased

Feature Extraction

text-generation-inference

Inference Endpoints

Model card Files Files and versions Community

huseinzol05 commited on Sep 5, 2021

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0254fae

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1 Parent(s): b870a17

fix readme

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README.md +4 -4

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@@ -35,8 +35,8 @@ You can use this model by installing `torch` or `tensorflow` and Huggingface lib
 ```python
 from transformers import T5Tokenizer, T5Model
-model = T5Model.from_pretrained('malay-huggingface/t5-small-bahasa-cased')
-tokenizer = T5Tokenizer.from_pretrained('malay-huggingface/t5-small-bahasa-cased')
 ```
 ## Example using T5ForConditionalGeneration
@@ -44,8 +44,8 @@ tokenizer = T5Tokenizer.from_pretrained('malay-huggingface/t5-small-bahasa-cased
 ```python
 from transformers import T5Tokenizer, T5ForConditionalGeneration
-tokenizer = T5Tokenizer.from_pretrained('malay-huggingface/t5-small-bahasa-cased')
-model = T5ForConditionalGeneration.from_pretrained('malay-huggingface/t5-small-bahasa-cased')
 input_ids = tokenizer.encode('soalan: siapakah perdana menteri malaysia?', return_tensors = 'pt')
 outputs = model.generate(input_ids)
 print(tokenizer.decode(outputs[0]))

 ```python
 from transformers import T5Tokenizer, T5Model
+model = T5Model.from_pretrained('malay-huggingface/t5-super-tiny-bahasa-cased')
+tokenizer = T5Tokenizer.from_pretrained('malay-huggingface/t5-super-tiny-bahasa-cased')
 ```
 ## Example using T5ForConditionalGeneration
 ```python
 from transformers import T5Tokenizer, T5ForConditionalGeneration
+tokenizer = T5Tokenizer.from_pretrained('malay-huggingface/t5-super-tiny-bahasa-cased')
+model = T5ForConditionalGeneration.from_pretrained('malay-huggingface/t5-super-tiny-bahasa-cased')
 input_ids = tokenizer.encode('soalan: siapakah perdana menteri malaysia?', return_tensors = 'pt')
 outputs = model.generate(input_ids)
 print(tokenizer.decode(outputs[0]))