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@@ -8,14 +8,14 @@ language:
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  # EvoLLM-v1-JP-7B
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  <!-- Provide a quick summary of what the model is/does. -->
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- EvoLLM-v1-JP-7B is a evolved Japanese Math LLM.
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  ## Model Details
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  ### Model Description
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  <!-- Provide a longer summary of what this model is. -->
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- EvoLLM-v1-JP-7B is a Japanese Math LLM, merged the following source models in the Parameter Space (PS) by using an evolutionary approach.
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  - **Developed by:** [Sakana AI](https://sakana.ai/)
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  - **Model type:** Autoregressive Language Model
@@ -47,7 +47,7 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
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  # 1. load model
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  device = "cuda" if torch.cuda.is_available() else "CPU"
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- repo_id = "SakanaAI/EvoLLM-v1-JP-7B"
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  model = AutoModelForCausalLM.from_pretrained(repo_id, torch_dtype="auto")
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  tokenizer = AutoTokenizer.from_pretrained(repo_id)
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  model.to(device)
 
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  # EvoLLM-v1-JP-7B
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  <!-- Provide a quick summary of what the model is/does. -->
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+ EvoLLM-JP-v1-7B is a evolved Japanese Math LLM.
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  ## Model Details
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  ### Model Description
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  <!-- Provide a longer summary of what this model is. -->
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+ EvoLLM-JP-v1-7B is a Japanese Math LLM, merged the following source models in the Parameter Space (PS) by using an evolutionary approach.
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  - **Developed by:** [Sakana AI](https://sakana.ai/)
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  - **Model type:** Autoregressive Language Model
 
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  # 1. load model
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  device = "cuda" if torch.cuda.is_available() else "CPU"
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+ repo_id = "SakanaAI/EvoLLM-JP-v1-7B"
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  model = AutoModelForCausalLM.from_pretrained(repo_id, torch_dtype="auto")
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  tokenizer = AutoTokenizer.from_pretrained(repo_id)
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  model.to(device)