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README.md

@@ -25,7 +25,7 @@ You can then generate text as follows:
 ```python
 from transformers import pipeline
 
-generator = pipeline("text-generation", model="Jennny//tmp/tmp31k24y3o/Jennny/llama3_samsum_marl_wo_comm")
+generator = pipeline("text-generation", model="Jennny//tmp/tmp6ezz_1v5/Jennny/llama3_samsum_marl_wo_comm")
 outputs = generator("Hello, my llama is cute")
 ```
 
@@ -35,8 +35,8 @@ If you want to use the model for training or to obtain the outputs from the valu
 from transformers import AutoTokenizer
 from trl import AutoModelForCausalLMWithValueHead
 
-tokenizer = AutoTokenizer.from_pretrained("Jennny//tmp/tmp31k24y3o/Jennny/llama3_samsum_marl_wo_comm")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("Jennny//tmp/tmp31k24y3o/Jennny/llama3_samsum_marl_wo_comm")
+tokenizer = AutoTokenizer.from_pretrained("Jennny//tmp/tmp6ezz_1v5/Jennny/llama3_samsum_marl_wo_comm")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("Jennny//tmp/tmp6ezz_1v5/Jennny/llama3_samsum_marl_wo_comm")
 
 inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
 outputs = model(**inputs, labels=inputs["input_ids"])

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