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Chengxb888
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Update app.py
Browse files
app.py
CHANGED
@@ -10,6 +10,7 @@ def greet_json():
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@app.get("/hello/{msg}")
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def say_hello(msg: str):
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torch.random.manual_seed(0)
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model = AutoModelForCausalLM.from_pretrained(
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"microsoft/Phi-3-mini-128k-instruct",
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@@ -17,7 +18,7 @@ def say_hello(msg: str):
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torch_dtype="auto",
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trust_remote_code=True,
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)
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-
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tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-128k-instruct")
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messages = [
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@@ -26,13 +27,13 @@ def say_hello(msg: str):
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{"role": "assistant", "content": "Sure! Here are some ways to eat bananas and dragonfruits together: 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey. 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey."},
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{"role": "user", "content": msg},
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]
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-
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pipe = pipeline(
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"text-generation",
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model=model,
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tokenizer=tokenizer,
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)
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generation_args = {
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"max_new_tokens": 500,
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"return_full_text": False,
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@@ -41,4 +42,5 @@ def say_hello(msg: str):
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}
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output = pipe(messages, **generation_args)
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return {"message": output[0]['generated_text']}
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@app.get("/hello/{msg}")
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def say_hello(msg: str):
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print("model")
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torch.random.manual_seed(0)
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model = AutoModelForCausalLM.from_pretrained(
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"microsoft/Phi-3-mini-128k-instruct",
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torch_dtype="auto",
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trust_remote_code=True,
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)
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print("token & msg")
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tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-128k-instruct")
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messages = [
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{"role": "assistant", "content": "Sure! Here are some ways to eat bananas and dragonfruits together: 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey. 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey."},
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{"role": "user", "content": msg},
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]
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print("pipe")
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pipe = pipeline(
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"text-generation",
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model=model,
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tokenizer=tokenizer,
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)
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print("output")
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generation_args = {
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"max_new_tokens": 500,
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"return_full_text": False,
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}
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output = pipe(messages, **generation_args)
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print("complete")
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return {"message": output[0]['generated_text']}
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