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Update app.py
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app.py
CHANGED
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@@ -7,8 +7,7 @@ MODEL_NAME = "beyoru/Qwen3-0.9B-A0.6B"
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tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
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model = AutoModelForCausalLM.from_pretrained(
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MODEL_NAME,
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torch_dtype=torch.
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device_map="auto"
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)
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# --- Chat function ---
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@@ -30,7 +29,7 @@ def chat_fn(message, history, num_ctx, temperature, repeat_penalty, min_p, top_k
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outputs = model.generate(
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**inputs,
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max_new_tokens=
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temperature=float(temperature),
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top_p=float(top_p),
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top_k=int(top_k),
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@@ -51,7 +50,7 @@ with gr.Blocks(fill_height=True, fill_width=True) as app:
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gr.Markdown("## Qwen3 Playground (Transformers Edition)")
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gr.Markdown("Model: **beyoru/Qwen3-0.9B-A0.6B** — chạy trực tiếp bằng Transformers")
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num_ctx = gr.Slider(512, 8192,
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temperature = gr.Slider(0.1, 2.0, 0.6, 0.1, label="Temperature")
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repeat_penalty = gr.Slider(0.1, 2.0, 1.0, 0.1, label="Repeat Penalty")
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min_p = gr.Slider(0.0, 1.0, 0.0, 0.01, label="Min P")
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tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
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model = AutoModelForCausalLM.from_pretrained(
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MODEL_NAME,
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torch_dtype=torch.float16,
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)
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# --- Chat function ---
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outputs = model.generate(
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**inputs,
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max_new_tokens=2048,
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temperature=float(temperature),
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top_p=float(top_p),
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top_k=int(top_k),
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gr.Markdown("## Qwen3 Playground (Transformers Edition)")
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gr.Markdown("Model: **beyoru/Qwen3-0.9B-A0.6B** — chạy trực tiếp bằng Transformers")
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num_ctx = gr.Slider(512, 8192, 2048, 128, label="Context Length (num_ctx)")
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temperature = gr.Slider(0.1, 2.0, 0.6, 0.1, label="Temperature")
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repeat_penalty = gr.Slider(0.1, 2.0, 1.0, 0.1, label="Repeat Penalty")
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min_p = gr.Slider(0.0, 1.0, 0.0, 0.01, label="Min P")
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