google
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flan-t5-base

Text2Text Generation

Inference Endpoints

text-generation-inference

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Update README.md

#3

by ybelkada HF staff - opened Oct 22, 2022

base: refs/heads/main

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from: refs/pr/3

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README.md +4 -4

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@@ -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]))