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Update app.py
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app.py
CHANGED
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@@ -45,8 +45,8 @@ def build_prompt(req1, req2, prompt_type="zero-shot"):
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# -----------------------------
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@app.on_event("startup")
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def load_models():
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print("Loading DeepSeek model into memory...")
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deepseek_name = "deepseek-ai/
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app.state.deepseek_tokenizer = AutoTokenizer.from_pretrained(deepseek_name)
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app.state.deepseek_tokenizer.pad_token = app.state.deepseek_tokenizer.eos_token
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app.state.deepseek_model = AutoModelForCausalLM.from_pretrained(
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@@ -68,16 +68,12 @@ def run_gpt4(req1, req2, prompt_type, api_key):
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)
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return completion.choices[0].message.content.strip()
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def run_deepseek(req1, req2, prompt_type):
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tokenizer = app.state.deepseek_tokenizer
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model = app.state.deepseek_model
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prompt = build_prompt(req1, req2, prompt_type)
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inputs = tokenizer(
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[prompt],
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return_tensors="pt",
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padding=True,
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truncation=True
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)
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outputs = model.generate(
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input_ids=inputs.input_ids,
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attention_mask=inputs.attention_mask,
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# -----------------------------
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@app.on_event("startup")
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def load_models():
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print("Loading smaller DeepSeek model into memory...")
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deepseek_name = "deepseek-ai/deepseek-vl2-small" # smaller model
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app.state.deepseek_tokenizer = AutoTokenizer.from_pretrained(deepseek_name)
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app.state.deepseek_tokenizer.pad_token = app.state.deepseek_tokenizer.eos_token
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app.state.deepseek_model = AutoModelForCausalLM.from_pretrained(
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)
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return completion.choices[0].message.content.strip()
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+
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def run_deepseek(req1, req2, prompt_type):
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tokenizer = app.state.deepseek_tokenizer
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model = app.state.deepseek_model
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prompt = build_prompt(req1, req2, prompt_type)
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inputs = tokenizer([prompt], return_tensors="pt", padding=True, truncation=True)
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outputs = model.generate(
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input_ids=inputs.input_ids,
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attention_mask=inputs.attention_mask,
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