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  1. README.md +3 -5
README.md CHANGED
@@ -239,19 +239,17 @@ Then, copy the code snippet below to run the example.
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  ```python
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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- device = "auto"
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  model_path = "ibm-granite/granite-3.0-3b-a800m-base"
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  tokenizer = AutoTokenizer.from_pretrained(model_path)
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  # drop device_map if running on CPU
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- model = AutoModelForCausalLM.from_pretrained(model_path, device_map=device)
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  model.eval()
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  # change input text as desired
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  input_text = "Where is the MIT-IBM Watson AI Lab located?"
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  # tokenize the text
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- input_tokens = tokenizer(input_text, return_tensors="pt").to(device)
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  # generate output tokens
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- output = model.generate(**input_tokens,
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- max_length=4000)
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  # decode output tokens into text
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  output = tokenizer.batch_decode(output)
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  # print output
 
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  ```python
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  from transformers import AutoModelForCausalLM, AutoTokenizer
 
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  model_path = "ibm-granite/granite-3.0-3b-a800m-base"
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  tokenizer = AutoTokenizer.from_pretrained(model_path)
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  # drop device_map if running on CPU
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+ model = AutoModelForCausalLM.from_pretrained(model_path, device_map="auto")
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  model.eval()
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  # change input text as desired
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  input_text = "Where is the MIT-IBM Watson AI Lab located?"
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  # tokenize the text
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+ input_tokens = tokenizer(input_text, return_tensors="pt").to(model.device)
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  # generate output tokens
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+ output = model.generate(**input_tokens, max_length=4000)
 
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  # decode output tokens into text
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  output = tokenizer.batch_decode(output)
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  # print output