google
/

flan-t5-base

Text2Text Generation

text-generation-inference

Inference Endpoints

Model card Files Files and versions Community

ybelkada commited on Oct 22, 2022

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98d1823

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1 Parent(s): d2de2da

Update README.md (#3)

- Update README.md (eaf5c16955459b3c599a94c806187ce7e4df0ae8)

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README.md +4 -4

README.md CHANGED Viewed

@@ -159,7 +159,7 @@ tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-base")
 model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-base")
 input_text = "translate English to German: How old are you?"
-input_ids = tokenizer.encode(input_text, return_tensors="pt").input_ids
 outputs = model.generate(input_ids)
 print(tokenizer.decode(outputs[0]))
@@ -180,7 +180,7 @@ tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-base")
 model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-base", device_map="auto")
 input_text = "translate English to German: How old are you?"
-input_ids = tokenizer.encode(input_text, return_tensors="pt").input_ids.to("cuda")
 outputs = model.generate(input_ids)
 print(tokenizer.decode(outputs[0]))
@@ -204,7 +204,7 @@ tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-base")
 model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-base", device_map="auto", torch_dtype=torch.float16)
 input_text = "translate English to German: How old are you?"
-input_ids = tokenizer.encode(input_text, return_tensors="pt").input_ids.to("cuda")
 outputs = model.generate(input_ids)
 print(tokenizer.decode(outputs[0]))
@@ -225,7 +225,7 @@ tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-base")
 model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-base", device_map="auto", load_in_8bit=True)
 input_text = "translate English to German: How old are you?"
-input_ids = tokenizer.encode(input_text, return_tensors="pt").input_ids.to("cuda")
 outputs = model.generate(input_ids)
 print(tokenizer.decode(outputs[0]))

 model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-base")
 input_text = "translate English to German: How old are you?"
+input_ids = tokenizer(input_text, return_tensors="pt").input_ids
 outputs = model.generate(input_ids)
 print(tokenizer.decode(outputs[0]))
 model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-base", device_map="auto")
 input_text = "translate English to German: How old are you?"
+input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
 outputs = model.generate(input_ids)
 print(tokenizer.decode(outputs[0]))
 model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-base", device_map="auto", torch_dtype=torch.float16)
 input_text = "translate English to German: How old are you?"
+input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
 outputs = model.generate(input_ids)
 print(tokenizer.decode(outputs[0]))
 model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-base", device_map="auto", load_in_8bit=True)
 input_text = "translate English to German: How old are you?"
+input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
 outputs = model.generate(input_ids)
 print(tokenizer.decode(outputs[0]))