diff --git a/bot.py b/bot.py
index c2a2530..8840a28 100644
--- a/bot.py
+++ b/bot.py
@@ -1,37 +1,31 @@
 from argparse import ArgumentParser
 
-import torch
 from mastodon import Mastodon
-
-from dataset import Dataset
-from model import Model
-from predict import predict
+from transformers import AutoTokenizer, AutoModelForCausalLM
 
 
 parser = ArgumentParser()
 parser.add_argument('-t', '--token', help='Mastodon application access token')
-parser.add_argument('-i', '--input', default='data',
-                    help='training data input file')
-parser.add_argument('-e', '--text', default='i am',
-                    help='initial text for prediction')
-parser.add_argument('-d', '--device', default='cpu',
-                    help='device to run the model with')
-parser.add_argument('-m', '--model', default='model.pt',
+parser.add_argument('-i', '--input', default='i am',
+                    help='initial input text for prediction')
+parser.add_argument('-m', '--model', default='model',
                     help='path to load saved model')
 args = parser.parse_args()
 
 
+tokenizer = AutoTokenizer.from_pretrained('distilgpt2')
+model = AutoModelForCausalLM.from_pretrained(args.model)
+
+
+# Run the input through the model
+inputs = tokenizer.encode(args.input, return_tensors="pt")
+output = tokenizer.decode(model.generate(inputs, do_sample=True, max_length=25, top_p=0.9, temperature=0.8)[0])
+print(output)
+
+
+# Post it to Mastodon
 mastodon = Mastodon(
     access_token=args.token,
     api_base_url='https://social.exozy.me/'
 )
-
-
-dataset = Dataset(args.input, 32)
-device = torch.device(args.device)
-model = torch.load(args.model)
-
-
-text = predict(device, model, args.text)
-print(text)
-# mastodon.status_post(text)
+mastodon.status_post(output)
diff --git a/bot_lstm.py b/bot_lstm.py
new file mode 100644
index 0000000..c2a2530
--- /dev/null
+++ b/bot_lstm.py
@@ -0,0 +1,37 @@
+from argparse import ArgumentParser
+
+import torch
+from mastodon import Mastodon
+
+from dataset import Dataset
+from model import Model
+from predict import predict
+
+
+parser = ArgumentParser()
+parser.add_argument('-t', '--token', help='Mastodon application access token')
+parser.add_argument('-i', '--input', default='data',
+                    help='training data input file')
+parser.add_argument('-e', '--text', default='i am',
+                    help='initial text for prediction')
+parser.add_argument('-d', '--device', default='cpu',
+                    help='device to run the model with')
+parser.add_argument('-m', '--model', default='model.pt',
+                    help='path to load saved model')
+args = parser.parse_args()
+
+
+mastodon = Mastodon(
+    access_token=args.token,
+    api_base_url='https://social.exozy.me/'
+)
+
+
+dataset = Dataset(args.input, 32)
+device = torch.device(args.device)
+model = torch.load(args.model)
+
+
+text = predict(device, model, args.text)
+print(text)
+# mastodon.status_post(text)