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@@ -33,25 +33,6 @@ The model was finetuned using the Unsloth library, leveraging its efficient trai
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  - **Language**: English (`en`)
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  - **License**: Apache-2.0
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- ## Usage
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-
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- ### Loading the Model
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-
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- You can load the model and tokenizer using the following code snippet:
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-
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- ```python
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- from transformers import AutoModelForCausalLM, AutoTokenizer
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-
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- # Load the tokenizer and model
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- tokenizer = AutoTokenizer.from_pretrained("inetnuc/llama-3-8b-chat-nuclear")
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- model = AutoModelForCausalLM.from_pretrained("inetnuc/llama-3-8b-chat-nuclear")
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-
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- # Example of generating text
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- inputs = tokenizer("what is the iaea approach for cyber security?", return_tensors="pt")
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- outputs = model.generate(**inputs, max_new_tokens=128)
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- print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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-
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-
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  ## Files and Versions
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  | File Name | Description |
@@ -81,3 +62,25 @@ MUSTAFA UMUT OZBEK
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  ## Contact
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  https://www.linkedin.com/in/mustafaumutozbek/
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  https://x.com/m_umut_ozbek
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - **Language**: English (`en`)
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  - **License**: Apache-2.0
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  ## Files and Versions
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  | File Name | Description |
 
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  ## Contact
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  https://www.linkedin.com/in/mustafaumutozbek/
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  https://x.com/m_umut_ozbek
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+
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+
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+ ## Usage
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+
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+ ### Loading the Model
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+
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+ You can load the model and tokenizer using the following code snippet:
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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ # Load the tokenizer and model
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+ tokenizer = AutoTokenizer.from_pretrained("inetnuc/llama-3-8b-chat-nuclear")
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+ model = AutoModelForCausalLM.from_pretrained("inetnuc/llama-3-8b-chat-nuclear")
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+
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+ # Example of generating text
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+ inputs = tokenizer("what is the iaea approach for cyber security?", return_tensors="pt")
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+ outputs = model.generate(**inputs, max_new_tokens=128)
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+ print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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+
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+
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+