Update app.py
Browse files
app.py
CHANGED
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@@ -2,24 +2,29 @@ import gradio as gr
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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-
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# Load DeepSeek model
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model_id = "deepseek-ai/deepseek-llm-7b-chat"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16, device_map="auto")
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def generate_response(prompt):
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inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
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outputs = model.generate(
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**inputs,
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do_sample=True,
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temperature=
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top_p=0.9
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)
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return tokenizer.decode(outputs[0], skip_special_tokens=True)
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# return "Hello " + name + "!!"
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demo = gr.Interface(fn=generate_response,
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demo.launch()
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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# Load DeepSeek model
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model_id = "deepseek-ai/deepseek-llm-7b-chat"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16, device_map="auto")
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def generate_response(prompt, temperature):
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inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
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outputs = model.generate(
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**inputs,
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do_sample=True,
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temperature=temperature,
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top_p=0.9
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)
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return tokenizer.decode(outputs[0], skip_special_tokens=True)
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# return "Hello " + name + "!!"
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demo = gr.Interface(fn=generate_response,
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inputs=[
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gr.Textbox(label="Prompt", lines=6, placeholder="Ask something..."),
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gr.Slider(0.1, 1.5, value=0.7, step=0.1, label="Temperature")
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],
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outputs="text"
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)
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demo.launch()
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