Create app.py

app.py

@@ -0,0 +1,55 @@
+import gradio as gr
+from transformers import AutoTokenizer
+
+# List of supported Qwen3 models
+QWEN_MODELS = [
+    "Qwen/Qwen3-0.6B",
+    "Qwen/Qwen3-1.7B",
+    "Qwen/Qwen3-14B",
+    "Qwen/Qwen3-235B-A22B",
+    "Qwen/Qwen3-30B-A3B",
+    "Qwen/Qwen3-32B",
+    "Qwen/Qwen3-4B"
+]
+
+# Cache tokenizers to avoid repeated downloads
+tokenizer_cache = {}
+
+def count_tokens(model_name, text_input, file_input):
+    # Read text from uploaded file if provided
+    if file_input is not None:
+        text = file_input.read().decode("utf-8")
+    else:
+        text = text_input
+
+    if not text.strip():
+        return 0, []
+
+    # Load tokenizer (with caching)
+    if model_name not in tokenizer_cache:
+        tokenizer_cache[model_name] = AutoTokenizer.from_pretrained(
+            model_name, trust_remote_code=True
+        )
+    tokenizer = tokenizer_cache[model_name]
+
+    # Tokenization
+    token_ids = tokenizer.encode(text, add_special_tokens=False)
+    tokens = tokenizer.convert_ids_to_tokens(token_ids)
+
+    return len(token_ids), tokens
+
+# Gradio UI
+gr.Interface(
+    fn=count_tokens,
+    inputs=[
+        gr.Dropdown(choices=QWEN_MODELS, label="Select Qwen Model", value=QWEN_MODELS[0]),
+        gr.Textbox(lines=5, label="Input Text (ignored if file is uploaded)"),
+        gr.File(label="Upload .txt File (optional)", file_types=[".txt"])
+    ],
+    outputs=[
+        gr.Number(label="Token Count"),
+        gr.JSON(label="Tokens")
+    ],
+    title="Qwen Token Counter",
+    description="Select a Qwen model and input text or upload a .txt file to see token count and token list."
+).launch()