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cab7f8a
1
Parent(s): 1549b17
update commit with phi-3 mini 1114
Browse files
app.py
CHANGED
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@@ -1,26 +1,22 @@
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import gradio as gr
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
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# ✅
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try:
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print(f"⚠️ GPU allocation failed: {e}")
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#
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model_id = "microsoft/phi-3-mini-4k-instruct"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
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device_map="auto"
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)
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pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
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#
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def chat_fn(message, history):
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history_text = ""
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for item in history:
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@@ -33,18 +29,14 @@ def chat_fn(message, history):
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result = pipe(prompt, max_new_tokens=512, do_sample=True, temperature=0.7)[0]['generated_text']
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reply = result.split("<|assistant|>")[-1].strip()
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if "```" not in reply and any(w in reply for w in ["def ", "class ", "import "]):
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reply = f"```\n{reply}\n```"
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return reply
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#
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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gr.Markdown("## 💬 Chat with Phi-3 Mini")
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gr.Markdown(
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"Welcome to your AI Assistant powered by Phi-3 Mini and ZeroGPU (uses GPU if available)."
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)
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gr.ChatInterface(
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fn=chat_fn,
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@@ -57,5 +49,4 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
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chatbot=gr.Chatbot(type="messages")
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)
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demo.launch(ssr_mode=False)
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import gradio as gr
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from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
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# ✅ Safe import of the GPU decorator
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try:
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from spaces import GPU
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except ImportError:
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def GPU(func): return func # Fallback if not in a HF Space
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# ✅ Load Phi-3 Mini model
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model_id = "microsoft/phi-3-mini-4k-instruct"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(
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model_id, torch_dtype="auto", device_map="auto"
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)
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pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
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# ✅ Apply GPU decorator to ensure ZeroGPU allocates GPU
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@GPU
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def chat_fn(message, history):
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history_text = ""
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for item in history:
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result = pipe(prompt, max_new_tokens=512, do_sample=True, temperature=0.7)[0]['generated_text']
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reply = result.split("<|assistant|>")[-1].strip()
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if "```" not in reply and any(word in reply for word in ["def ", "class ", "import "]):
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reply = f"```\n{reply}\n```"
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return reply
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# ✅ Gradio UI
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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gr.Markdown("## 💬 Chat with Phi-3 Mini")
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gr.Markdown("Welcome to your AI Assistant powered by Phi-3 Mini. Ask me anything or request code examples!")
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gr.ChatInterface(
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fn=chat_fn,
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chatbot=gr.Chatbot(type="messages")
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)
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demo.launch()
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