Create README.md

README.md

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+```
+import transformers
+from transformers import (
+    AutoConfig,
+    AutoModelForSequenceClassification,
+    AutoTokenizer,
+    DataCollatorWithPadding,
+    EvalPrediction,
+    HfArgumentParser,
+    PretrainedConfig,
+    Trainer,
+    TrainingArguments,
+    default_data_collator,
+    set_seed,
+)
+import torch
+
+model_dir = "nealcly/detection-longformer"
+tokenizer = AutoTokenizer.from_pretrained(model_dir)
+model = AutoModelForSequenceClassification.from_pretrained(model_dir).to('cuda:0')
+threshold = 3.08583984375
+label2decisions = {
+    0: "machine-generated",
+    1: "human-written",
+}
+
+def detect(input_text):
+    tokenize_input = tokenizer(input_text)
+    tensor_input = torch.tensor([tokenize_input["input_ids"]]).to('cuda:0')
+    outputs = model(tensor_input)
+    is_machine = -outputs.logits[0][0].item() + threshold
+    if is_machine > 0:
+        decision = 0
+    else:
+        decision = 1
+    print(f"The text is {label2decisions[decision]}.")
+```