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Mar2Ding
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songcomposer_sft

Text Generation
Transformers
PyTorch
English
Chinese
internlm
feature-extraction
custom_code
Model card Files
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 Community
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  ---
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  license: apache-2.0
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  pipeline_tag: text-generation
 
 
 
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  ---
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@@ -29,7 +32,7 @@ We release SongComposer series in two versions:
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  To load the SongComposer_sft model using Transformers, use the following code:
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  ```python
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  from transformers import AutoTokenizer, AutoModelForCausalLM
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- ckpt_path = "Mar2Ding/songcomposer_pretrain"
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  tokenizer = AutoTokenizer.from_pretrained(ckpt_path, trust_remote_code=True)
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  model = AutoModel.from_pretrained(ckpt_path, trust_remote_code=True).cuda().half()
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  prompt = 'Create a song on brave and sacrificing with a rapid pace.'
@@ -41,7 +44,7 @@ model.inference(prompt, tokenizer)
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  ```python
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  from transformers import AutoTokenizer, AutoModelForCausalLM
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- ckpt_path = "Mar2Ding/songcomposer_pretrain"
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  tokenizer = AutoTokenizer.from_pretrained(ckpt_path, trust_remote_code=True)
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  model = AutoModel.from_pretrained(ckpt_path, trust_remote_code=True).cuda().half()
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  prompt = 'Create a song on brave and sacrificing with a rapid pace.'
 
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  ---
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  license: apache-2.0
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  pipeline_tag: text-generation
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+ language:
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+ - en
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+ - zh
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  ---
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  To load the SongComposer_sft model using Transformers, use the following code:
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  ```python
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  from transformers import AutoTokenizer, AutoModelForCausalLM
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+ ckpt_path = "Mar2Ding/songcomposer_sft"
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  tokenizer = AutoTokenizer.from_pretrained(ckpt_path, trust_remote_code=True)
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  model = AutoModel.from_pretrained(ckpt_path, trust_remote_code=True).cuda().half()
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  prompt = 'Create a song on brave and sacrificing with a rapid pace.'
 
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  ```python
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  from transformers import AutoTokenizer, AutoModelForCausalLM
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+ ckpt_path = "Mar2Ding/songcomposer_sft"
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  tokenizer = AutoTokenizer.from_pretrained(ckpt_path, trust_remote_code=True)
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  model = AutoModel.from_pretrained(ckpt_path, trust_remote_code=True).cuda().half()
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  prompt = 'Create a song on brave and sacrificing with a rapid pace.'