main file

app.py

@@ -0,0 +1,55 @@
+
+hf_token="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"
+
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "meta-llama/Llama-2-13b-chat-hf"
+
+# load the model using 4bit quantization (https://huggingface.co/blog/4bit-transformers-bitsandbytes)
+model = AutoModelForCausalLM.from_pretrained(model_id, load_in_4bit=True, use_auth_token=hf_token)
+# disable Tensor Parallelism (https://github.com/huggingface/transformers/pull/24906)
+model.config.pretraining_tp=1
+
+tokenizer = AutoTokenizer.from_pretrained (model_id, use_auth_token=hf_token)
+
+def extract_lyrics(text):
+    start_index = text.find("Verse 1:")
+    end_index = text.find("</s>")
+    if start_index == -1:
+        return text
+
+    text = text[start_index:end_index].strip()
+
+    text = text.replace("</s>", "")
+
+    return text
+
+def generate_lyrics_test(content, sentiment):
+    # input_text = "Generate lyrics in standard song format that matches with following requirements. Content should be " + content + ". Genre should be " + genre +  ". Sentiment of the song should be " + sentiment.lower()
+    input_text = "Generate lyrics in standard song format that matches with following requirements. Content should be " + content + ". Sentiment of the song should be " + sentiment.lower()
+
+    input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
+    outputs = model.generate(input_ids, max_length=500)
+    return extract_lyrics(tokenizer.decode(outputs[0]))
+
+import gradio as gr
+
+demo = gr.Interface(
+    generate_lyrics_test,
+    [
+        gr.Textbox(lines=5, label = "Content"),
+        gr.Dropdown(
+            ["Positive", "Negative", "Neutral"], label = "Sentiment"
+        ),
+    ],
+    "text"
+)
+
+demo.queue().launch( )
+
+sentiment = 'Positive'
+# content = 'create a similar lyric to beat it from michael jackson and write something motivational instead'
+content = 'create a similar lyric to beat it from Michael Jackson and write something motivational instead'
+# genre = "Rock"
+input_text = "Generate lyrics in standard song format that matches with following requirements. Content should be " + content + ". Sentiment of the song should be " + sentiment.lower()
+print('input_text:', input_text)