Update README.md

README.md

@@ -25,6 +25,57 @@ margin. Our work reveals that LLMs can be an excellent compressor for music, but
 
 <!-- <audio controls src="https://cdn-uploads.huggingface.co/production/uploads/5fd6f670053c8345eddc1b68/8NSONUjIF7KGUCfwzPCd9.mpga"></audio> -->
 
+## Usage
+
+You can use the models through Huggingface's Transformers library. Check our Github repo for more advanced use: [https://github.com/hf-lin/ChatMusician](https://github.com/hf-lin/ChatMusician)
+
+## CLI demo
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig
+from string import Template
+prompt_template = Template("Human: ${inst} </s> Assistant: ")
+
+tokenizer = AutoTokenizer.from_pretrained("m-a-p/ChatMusician-v1-sft-78k", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("m-a-p/ChatMusician-v1-sft-78k", trust_remote_code=True).eval()
+model.cuda()
+generation_config = GenerationConfig(
+    temperature=0.2,
+    top_k=40,
+    top_p=0.9,
+    do_sample=True,
+    num_beams=1,
+    repetition_penalty=1.1,
+    min_new_tokens=10,
+    max_new_tokens=1536
+)
+
+instruction = """Using ABC notation, recreate the given text as a musical score.
+Meter C
+Notes The parts are commonly interchanged.
+Transcription 1997 by John Chambers
+Key D
+Note Length 1/8
+Rhythm reel
+"""
+
+prompt = prompt_template.safe_substitute({"inst": instruction})
+inputs = tokenizer(prompt, return_tensors="pt", add_special_tokens=False)
+response = model.generate(
+        input_ids=inputs["input_ids"].to(model.device),
+        attention_mask=inputs['attention_mask'].to(model.device),
+        eos_token_id=tokenizer.eos_token_id,
+        generation_config=generation_config,
+        )
+response = tokenizer.decode(response[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True)
+print(response)
+```
+
+## Limitations
+- For the music tasks, the model currently only supports strict format and close-ended instructions.
+- The model suffers from hallucinations, and shouldn't be used for music education.
+- A large proportion of the training data is in the style of Irish music.
+- The MusicThoeryBench results reported in the paper are obtained with perplexity mode. 
+
 ## Example Prompts
 
 **Our model produces symbolic music(ABC notation) well in the following prompts.** Here are some musical tasks.
@@ -144,56 +195,7 @@ We included GPT-3.5, GPT-4, LLaMA2-7B-Base, ChatMusician-Base, and ChatMusician.
 2. General language abilities of ChatMusician are evaluated  on the [Massive Multitask Language Understanding (MMLU) dataset](https://huggingface.co/datasets/lukaemon/mmlu).
 
 
-## Usage
-
-You can use the models through Huggingface's Transformers library. Check our Github repo for more advanced use: [https://github.com/hf-lin/ChatMusician](https://github.com/hf-lin/ChatMusician)
-
-## CLI demo
-```python
-from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig
-from string import Template
-prompt_template = Template("Human: ${inst} </s> Assistant: ")
-
-tokenizer = AutoTokenizer.from_pretrained("m-a-p/ChatMusician-v1-sft-78k", trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained("m-a-p/ChatMusician-v1-sft-78k", trust_remote_code=True).eval()
-model.cuda()
-generation_config = GenerationConfig(
-    temperature=0.2,
-    top_k=40,
-    top_p=0.9,
-    do_sample=True,
-    num_beams=1,
-    repetition_penalty=1.1,
-    min_new_tokens=10,
-    max_new_tokens=1536
-)
-
-instruction = """Using ABC notation, recreate the given text as a musical score.
-Meter C
-Notes The parts are commonly interchanged.
-Transcription 1997 by John Chambers
-Key D
-Note Length 1/8
-Rhythm reel
-"""
-
-prompt = prompt_template.safe_substitute({"inst": instruction})
-inputs = tokenizer(prompt, return_tensors="pt", add_special_tokens=False)
-response = model.generate(
-        input_ids=inputs["input_ids"].to(model.device),
-        attention_mask=inputs['attention_mask'].to(model.device),
-        eos_token_id=tokenizer.eos_token_id,
-        generation_config=generation_config,
-        )
-response = tokenizer.decode(response[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True)
-print(response)
-```
 
-## Limitations
-- For the music tasks, the model currently only supports strict format and close-ended instructions.
-- The model suffers from hallucinations, and shouldn't be used for music education.
-- A large proportion of the training data is in the style of Irish music.
-- The MusicThoeryBench results reported in the paper are obtained with perplexity mode. 
 
 ## Citation
 If you find our work helpful, feel free to give us a cite.