Update README.md

README.md

@@ -25,15 +25,15 @@ pipeline_tag: text-generation
 
 </div>
 
-**SongComposer** is a language large model (VLLM) based on [InternLM2](https://github.com/InternLM/InternLM) for lyric and melody composition in song generation. 
+**SongComposer** is a language large model (LLM) based on [InternLM2](https://github.com/InternLM/InternLM) for lyric and melody composition in song generation. 
 
 We release SongComposer series in two versions:
 
-- SongComposer_pretrain: The pretrained SongComposer with InternLM2 as the initialization of the LLM, gain basic knowledge on lyric and melody.
+- SongComposer_pretrain: The pretrained SongComposer with InternLM2 as the initialization of the LLM, gains basic knowledge of lyric and melody.
 - SongComposer_sft: The finetuned SongComposer for *instruction-following song generation* including lyric to melody, melody to lyric, song continuation, text to song.
 
 ### Import from Transformers
-To load the SongComposer_sft model using Transformers, use the following code:
+To load the SongComposer_pretrain model using Transformers, use the following code:
 ```python
 from transformers import AutoTokenizer, AutoModelForCausalLM
 ckpt_path = "Mar2Ding/songcomposer_pretrain"
@@ -41,12 +41,11 @@ tokenizer = AutoTokenizer.from_pretrained(ckpt_path, trust_remote_code=True)
 model = AutoModel.from_pretrained(ckpt_path, trust_remote_code=True).cuda().half()
 from modeling_internlm2 import inference_pretrain
 prompt = '<bop> Total 7 lines. The first line:可,<D4>,<137>,<79>|惜,<D#4>,<137>,<79>|这,<F4>,<137>,<88>|是,<F4>,<121>,<79>|属,<F4>,<121>,<79>|于,<D#4>,<214>,<88>|你,<D#4>,<141>,<79>|的,<D4>,<130>,<79>|风,<C4>,<151>,<79>|景,<A#3> <F3>,<181><137>,<79>\n'
-inference_pretrain(prompt, tokenizer, model)
+model.inference_pretrain(prompt, tokenizer, model)
 ```
 
 ### 通过 Transformers 加载
-通过以下的代码加载 SongComposer_sft 模型
-
+通过以下的代码加载 SongComposer_pretrain 模型
 ```python
 from transformers import AutoTokenizer, AutoModelForCausalLM
 ckpt_path = "Mar2Ding/songcomposer_pretrain"
@@ -54,7 +53,7 @@ tokenizer = AutoTokenizer.from_pretrained(ckpt_path, trust_remote_code=True)
 model = AutoModel.from_pretrained(ckpt_path, trust_remote_code=True).cuda().half()
 from modeling_internlm2 import inference_pretrain
 prompt = '<bop> Total 7 lines. The first line:可,<D4>,<137>,<79>|惜,<D#4>,<137>,<79>|这,<F4>,<137>,<88>|是,<F4>,<121>,<79>|属,<F4>,<121>,<79>|于,<D#4>,<214>,<88>|你,<D#4>,<141>,<79>|的,<D4>,<130>,<79>|风,<C4>,<151>,<79>|景,<A#3> <F3>,<181><137>,<79>\n'
-inference_pretrain(prompt, tokenizer, model)
+model.inference_pretrain(prompt, tokenizer, model)
 ```
 
 ### Open Source License