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google
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flan-t5-xl

Transformers
PyTorch
TensorFlow
JAX
Safetensors
t5
text2text-generation
text-generation-inference
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Update README.md

#2
by ybelkada - opened
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  1. README.md +4 -4
README.md CHANGED
@@ -158,7 +158,7 @@ tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-xl")
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  model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-xl")
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  input_text = "translate English to German: How old are you?"
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- input_ids = tokenizer.encode(input_text, return_tensors="pt").input_ids
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  outputs = model.generate(input_ids)
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  print(tokenizer.decode(outputs[0]))
@@ -179,7 +179,7 @@ tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-xl")
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  model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-xl", device_map="auto")
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  input_text = "translate English to German: How old are you?"
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- input_ids = tokenizer.encode(input_text, return_tensors="pt").input_ids.to("cuda")
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  outputs = model.generate(input_ids)
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  print(tokenizer.decode(outputs[0]))
@@ -203,7 +203,7 @@ tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-xl")
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  model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-xl", device_map="auto", torch_dtype=torch.float16)
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  input_text = "translate English to German: How old are you?"
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- input_ids = tokenizer.encode(input_text, return_tensors="pt").input_ids.to("cuda")
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  outputs = model.generate(input_ids)
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  print(tokenizer.decode(outputs[0]))
@@ -224,7 +224,7 @@ tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-xl")
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  model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-xl", device_map="auto", load_in_8bit=True)
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  input_text = "translate English to German: How old are you?"
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- input_ids = tokenizer.encode(input_text, return_tensors="pt").input_ids.to("cuda")
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  outputs = model.generate(input_ids)
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  print(tokenizer.decode(outputs[0]))
 
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  model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-xl")
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  input_text = "translate English to German: How old are you?"
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+ input_ids = tokenizer(input_text, return_tensors="pt").input_ids
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  outputs = model.generate(input_ids)
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  print(tokenizer.decode(outputs[0]))
 
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  model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-xl", device_map="auto")
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  input_text = "translate English to German: How old are you?"
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+ input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
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  outputs = model.generate(input_ids)
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  print(tokenizer.decode(outputs[0]))
 
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  model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-xl", device_map="auto", torch_dtype=torch.float16)
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  input_text = "translate English to German: How old are you?"
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+ input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
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  outputs = model.generate(input_ids)
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  print(tokenizer.decode(outputs[0]))
 
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  model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-xl", device_map="auto", load_in_8bit=True)
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  input_text = "translate English to German: How old are you?"
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+ input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
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  outputs = model.generate(input_ids)
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  print(tokenizer.decode(outputs[0]))