update

app.py

@@ -7,17 +7,17 @@ llm = Llama(model_path="ggml-model-f16-q4_0.bin", n_ctx=2048)
 
 def generate_text_instruct(input_text):
     response = ""
-    txt2tag_prompt = f"Provide me with danbooru tags that accurately describe the following description. {input_text}"
+    txt2tag_prompt = f"You are a tool that helps tag danbooru images when given a textual image description. Provide me with danbooru tags that accurately fit the following description. {input_text}"
     for output in llm(f"A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: {txt2tag_prompt} ASSISTANT: ", 
-                      echo=False, stream=True, stop=["</s>", "\n", "User:", "<unk>"]):
+                      echo=False, stream=True, max_tokens=64, stop=["</s>", "\n", "User:", "<unk>"]):
         answer = output['choices'][0]['text']
         response += answer
         yield response
 
 instruct_interface = gr.Interface(
     fn=generate_text_instruct,
-    inputs=gr.inputs.Textbox(lines= 10, label="Enter your instruction text"),
-    outputs=gr.outputs.Textbox(label="Output text"),
+    inputs=gr.inputs.Textbox(lines= 10, label="Enter your image description"),
+    outputs=gr.outputs.Textbox(label="danbooru tags"),
 )
 
 with gr.Blocks() as demo:

ggml-model-f16-q4_0.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:43c1bce0a7cf7c9debec8590c144ef2c831db8616704e698110065072a528a32
+oid sha256:a214d083617ae4cb2971d73235043d3505407017cd0d98639ee762618e09c177
 size 7323305088