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@@ -5,7 +5,7 @@ datasets:
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  - saillab/alpaca-maithili-cleaned
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  ---
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- # MISHANM/Maithili__text_generation_Llama3_8B_instruction
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  This model is fine-tuned for the Maithili language, capable of answering queries and translating text Between English and Maithili. It leverages advanced natural language processing techniques to provide accurate and context-aware responses.
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@@ -36,7 +36,7 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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  # Load the fine-tuned model and tokenizer
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- model_path = "MISHANM/Maithili__text_generation_Llama3_8B_instruction"
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  model = AutoModelForCausalLM.from_pretrained(model_path)
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  # Wrap the model with DataParallel if multiple GPUs are available
@@ -80,7 +80,7 @@ print(translated_text)
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  ## Citation Information
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  ```
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- @misc{MISHANM/Maithili__text_generation_Llama3_8B_instruction,
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  author = {Mishan Maurya},
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  title = {Introducing Fine Tuned LLM for Maithili Language},
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  year = {2024},
 
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  - saillab/alpaca-maithili-cleaned
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  ---
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+ # MISHANM/Maithili_text_generation_Llama3_8B_instruction
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  This model is fine-tuned for the Maithili language, capable of answering queries and translating text Between English and Maithili. It leverages advanced natural language processing techniques to provide accurate and context-aware responses.
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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  # Load the fine-tuned model and tokenizer
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+ model_path = "MISHANM/MISHANM/Maithili_text_generation_Llama3_8B_instruction"
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  model = AutoModelForCausalLM.from_pretrained(model_path)
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  # Wrap the model with DataParallel if multiple GPUs are available
 
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  ## Citation Information
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  ```
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+ @misc{MISHANM/MISHANM/Maithili_text_generation_Llama3_8B_instruction,
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  author = {Mishan Maurya},
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  title = {Introducing Fine Tuned LLM for Maithili Language},
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  year = {2024},