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--- |
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base_model: |
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- ifable/gemma-2-Ifable-9B |
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--- |
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Created with: |
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``` |
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from transformers import AutoModelForCausalLM |
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import torch |
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# 加载模型并解除共享 |
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model = AutoModelForCausalLM.from_pretrained("ifable/gemma-2-Ifable-9B", tie_word_embeddings=False) |
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# 解除共享的 lm_head 和 embed_tokens 权重 |
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model.lm_head.weight.data = model.model.embed_tokens.weight.data.clone() |
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# 将模型转换为 bf16 格式 |
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model = model.to(dtype=torch.bfloat16) |
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# 指定保存路径 |
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untied_model_dir = "mergekit/output" |
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# 保存解除共享且为 bf16 格式的模型 |
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model.save_pretrained(untied_model_dir) |
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model.config.save_pretrained(untied_model_dir) |
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``` |
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I didn't copy tokenizer from the original model, do it yourself if you want. |
