Create app.py

app.py

@@ -0,0 +1,46 @@
+import gradio as gr
+import json
+import httpx
+
+def geninference(model):
+    modelconfig = httpx.get(f'https://huggingface.co/{model}/raw/main/config.json')
+    jsonconfig = json.loads(modelconfig.text)
+    rawtokenizerconfig = httpx.get(f'https://huggingface.co/{model}/raw/main/tokenizer_config.json')
+    tokenizerconfig = json.loads(rawtokenizerconfig.text)
+    arch = jsonconfig["architectures"][0]
+    tokenizerclass = tokenizerconfig["tokenizer_class"]
+    inference_code = f"""
+    from transformers import {arch}, {tokenizerclass}
+
+    model_id = "{model}"
+
+    model = {arch}.from_pretrained(model_id)
+    tokenizer = {tokenizerclass}.from_pretrained(model_id)
+    prompt = "Hello"
+    inputs = tokenizer(prompt, return_tensors="pt")
+    gen_ids = model.generate(
+        inputs.input_ids,
+        max_length=50,
+        num_return_sequences=1,
+        no_repeat_ngram_size=2,
+        do_sample=True,
+        temperature=0.7,
+    )
+    output = tokenizer.decode(gen_ids[0], skip_special_tokens=True)
+    print(output)
+    """
+    return inference_code
+
+with gr.Blocks() as demo:
+    gr.Markdown("## Generate inference code for your model with a single click!")
+    with gr.Row(equal_height=True):
+        inputbox = gr.Textbox(placeholder="Enter your model id here", label="Model ID")
+        generatebtn = gr.Button("Generate", variant="primary")
+    outputbox = gr.Textbox(placeholder="Output will be here", label="output", interactive=False)
+    generatebtn.click(
+        fn=geninference,
+        inputs=inputbox,
+        outputs=outputbox
+    )
+
+demo.launch()