new models
Browse files
app.py
CHANGED
@@ -3,13 +3,18 @@ from llama_cpp import Llama
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# Load models
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llm = Llama.from_pretrained(
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-
repo_id="Robzy/
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filename="unsloth.Q4_K_M.gguf",
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)
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llm2 = Llama.from_pretrained(
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repo_id="Robzy/
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filename="unsloth.
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)
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# Define prediction functions
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@@ -62,7 +67,7 @@ def predict3(message, history, model):
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messages.append({"role": "user", "content": message})
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response = ""
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-
for chunk in
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stream=True,
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messages=messages,
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):
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@@ -75,12 +80,10 @@ def predict3(message, history, model):
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# Define ChatInterfaces
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io1 = gr.ChatInterface(predict, title="4-bit")
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io2 = gr.ChatInterface(predict2, title="
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io3 = gr.ChatInterface(predict3, title="
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io4 = gr.ChatInterface(predict2, title="32-bit") # Placeholder
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# Dropdown and visibility mapping
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chat_interfaces = {"4-bit": io1, "
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# Define UI
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with gr.Blocks() as demo:
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@@ -88,13 +91,9 @@ with gr.Blocks() as demo:
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with gr.Tab("4-bit"):
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io1.render()
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with gr.Tab("
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io2.render()
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with gr.Tab("
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io3.render()
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with gr.Tab("32-bit"):
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io4.render()
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-
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-
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demo.launch()
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# Load models
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llm = Llama.from_pretrained(
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repo_id="Robzy/lora_model_CodeData_120k",
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filename="unsloth.Q4_K_M.gguf",
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)
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llm2 = Llama.from_pretrained(
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repo_id="Robzy/lora_model_CodeData_120k",
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filename="unsloth.Q5_K_M.gguf",
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)
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llm3 = Llama.from_pretrained(
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repo_id="Robzy/lora_model_CodeData_120k",
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filename="unsloth.Q8_0.gguf",
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)
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# Define prediction functions
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messages.append({"role": "user", "content": message})
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response = ""
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for chunk in llm3.create_chat_completion(
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stream=True,
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messages=messages,
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):
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# Define ChatInterfaces
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io1 = gr.ChatInterface(predict, title="4-bit")
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io2 = gr.ChatInterface(predict2, title="5-bit") # Placeholder
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io3 = gr.ChatInterface(predict3, title="8-bit")
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# Dropdown and visibility mapping
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chat_interfaces = {"4-bit": io1, "5-bit": io2, "8-bit": io3}
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# Define UI
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with gr.Blocks() as demo:
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with gr.Tab("4-bit"):
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io1.render()
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with gr.Tab("5-bit"):
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io2.render()
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with gr.Tab("8-bit"):
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io3.render()
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demo.launch()
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