include comparison with hosted version

app.py

@@ -1,10 +1,19 @@
 import os
+import requests
 
 import gradio as gr
 import torch
-from transformers import RobertaForSequenceClassification, RobertaTokenizer, RobertaConfig
+from transformers import (
+    RobertaForSequenceClassification,
+    RobertaTokenizer,
+    RobertaConfig,
+)
 
-os.system("wget https://openaipublic.azureedge.net/gpt-2/detector-models/v1/detector-base.pt")
+HF_TOKEN = os.environ["HF_TOKEN"]
+
+os.system(
+    "wget https://openaipublic.azureedge.net/gpt-2/detector-models/v1/detector-base.pt"
+)
 
 config = RobertaConfig.from_pretrained("roberta-base")
 model = RobertaForSequenceClassification(config)
@@ -17,13 +26,36 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 model.to(device)
 
 
-def detect(query):
+def call_inference_api(query):
+    url = "https://api-inference.huggingface.co/models/roberta-base-openai-detector"
+
+    headers = {"Authorization": f"Bearer {HF_TOKEN}"}
+    response = requests.post(url, json={"inputs": query}, headers=headers)
+
+    code = response.status_code
+    if code == 200:
+        fake, real = response.json()[0]
+
+        fake_score = fake["score"]
+        real_score = real["score"]
+
+        return f"Fake: {fake_score:.2%} | Real: {real_score:.2%}"
+
+    else:
+        error = response.json()["error"]
+        warning = response.json()["warnings"]
+        return f"Error: {error} | Warning: {warning}"
+
+
+def local_call(query):
     # Copied from https://github.com/openai/gpt-2-output-dataset/tree/master/detector#L35-L46
     tokens = tokenizer.encode(query)
     all_tokens = len(tokens)
-    tokens = tokens[:tokenizer.max_len - 2]
+    tokens = tokens[: tokenizer.max_len - 2]
     used_tokens = len(tokens)
-    tokens = torch.tensor([tokenizer.bos_token_id] + tokens + [tokenizer.eos_token_id]).unsqueeze(0)
+    tokens = torch.tensor(
+        [tokenizer.bos_token_id] + tokens + [tokenizer.eos_token_id]
+    ).unsqueeze(0)
     mask = torch.ones_like(tokens)
 
     with torch.no_grad():
@@ -35,6 +67,32 @@ def detect(query):
     return f"Fake: {fake:.2%} | Real: {real:.2%} | Used tokens: {used_tokens} | All tokens: {all_tokens}"
 
 
-demo = gr.Interface(fn=detect, inputs="text", outputs="text")
+def main_function(query):
+    hosted_output = call_inference_api(query)
+    local_output = local_call(query)
+
+    return hosted_output, local_output
+
+
+text_input = gr.Textbox(
+    lines=5,
+    label="Enter text to compare output with the model hosted here: https://huggingface.co/roberta-base-openai-detector",
+)
+hosted_output = gr.Textbox(label="Output from model hosted on Hugging Face")
+local_output = gr.Textbox(
+    label="Output from model running locally on transformers 2.0.0, tokenizers 0.7.0, and torch 1.4.0"
+)
+
+description = "The original repository for the model used an older version of \
+transformers, tokenziers, and torch which results in slightly different results \
+    compared to the model hosted on Hugging Face. This app compares the two models."
+
+demo = gr.Interface(
+    fn=main_function,
+    inputs="text",
+    outputs=[hosted_output, local_output],
+    title="Compare OpenAI detector models",
+    description=description,
+)
 
-demo.launch()   
+demo.launch()