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@@ -31,7 +31,8 @@ The model is intended to be used for any analysis where the reputation (such as
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  You can use these models in your own applications by leveraging the Hugging Face Transformers library. Below is a Python code snippet demonstrating how to load and use the FT-News classification model:
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  ```python
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- from transformers import pipeline
 
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  # Load the model
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  model = AutoPeftModelForCausalLM.from_pretrained("Moritz-Pfeifer/financial-times-classification-llama-2-7b-v1.3")
 
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  You can use these models in your own applications by leveraging the Hugging Face Transformers library. Below is a Python code snippet demonstrating how to load and use the FT-News classification model:
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  ```python
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+ from peft import AutoPeftModelForCausalLM
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+ from transformers import AutoTokenizer, pipeline
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  # Load the model
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  model = AutoPeftModelForCausalLM.from_pretrained("Moritz-Pfeifer/financial-times-classification-llama-2-7b-v1.3")