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huggingface_nlp.py

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+import transformers
+transformers.__version__
+
+import torch
+torch.cuda.is_available()
+
+from transformers import pipeline
+
+generator = pipeline("text-generation")
+
+generator = pipeline("text-generation", model = "Qwen/Qwen3-4B-Instruct-2507",
+                     torch_dtype= "auto", device_map="auto")
+
+messages = [
+    {"role": "system", "content": "You are a helpful AI assistant."},
+    {"role": "user", "content": "Tell me a short joke"}
+]
+
+outputs = generator(
+    messages,
+    max_new_tokens = 100,
+    do_sample=True,
+    temperature = 0.7,
+    return_full_text = False)
+
+print(outputs[0]["generated_text"])
+
+messages = [
+    {"role": "system", "content": "You are a helpful AI assistant."},
+    {"role": "user", "content": "Türkiyenin başkenti neresidir?"}
+]
+
+outputs = generator(
+    messages,
+    max_new_tokens = 100,
+    do_sample=True,
+    temperature = 0.7,
+    return_full_text = False)
+
+print(outputs[0]["generated_text"])
+
+import gradio as gr
+
+def generate_text(prompt):
+  messages = [
+    {"role": "system", "content": "You are a helpful AI assistant."},
+    {"role": "user", "content": prompt}]
+  outputs = generator(
+    messages,
+    max_new_tokens = 100,
+    do_sample=True,
+    temperature = 0.7,
+    return_full_text = False)
+  return outputs[0]["generated_text"]
+
+demo = gr.Interface(
+    fn= generate_text,
+    inputs = gr.Textbox(label="Give an input"),
+    outputs = gr.Textbox(label="Output"),
+    title = "Text Generation"
+)
+
+demo.launch()
+

requirements.txt

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+torch
+transformers
+gradio
+accelerate
+safetensors