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@@ -6,8 +6,12 @@ license: apache-2.0
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  This is unsloth/llama-3-8b-Instruct trained on the Replete-AI/code-test-dataset using the code bellow with unsloth and google colab with under 15gb of vram. This training was complete in about 40 minutes total.
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  Copy from my announcement in my discord:
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- ```json
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- If anyone wants to train their own llama-3-8b model for free on any dataset that has around 1,500 lines of data or less you can now do it easily by using the code I provided in the model card for my test model in this repo and google colab. The training for this model uses (Unsloth + Qlora + Galore) to achieve the ability for training under such low vram.
 
 
 
 
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  ```
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  For anyone that is new to coding and training Ai, all your really have to edit is
@@ -85,6 +89,7 @@ model = FastLanguageModel.get_peft_model(
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  ```
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  ```Python
 
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  alpaca_prompt = """<|begin_of_text|><|start_header_id|>system<|end_header_id|>
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  Below is an instruction that describes a task, Write a response that appropriately completes the request.<|eot_id|><|start_header_id|>user<|end_header_id|>
 
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  This is unsloth/llama-3-8b-Instruct trained on the Replete-AI/code-test-dataset using the code bellow with unsloth and google colab with under 15gb of vram. This training was complete in about 40 minutes total.
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  Copy from my announcement in my discord:
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+ ```
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+ If anyone wants to train their own llama-3-8b model for free on any dataset
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+ that has around 1,500 lines of data or less you can now do it easily by using
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+ the code I provided in the model card for my test model in this repo and
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+ google colab. The training for this model uses (Unsloth + Qlora + Galore) to
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+ achieve the ability for training under such low vram.
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  ```
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  For anyone that is new to coding and training Ai, all your really have to edit is
 
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  ```
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  ```Python
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+
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  alpaca_prompt = """<|begin_of_text|><|start_header_id|>system<|end_header_id|>
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  Below is an instruction that describes a task, Write a response that appropriately completes the request.<|eot_id|><|start_header_id|>user<|end_header_id|>