From 6bab795fe83d683cc0bfbbc875ccdef70fb4112c Mon Sep 17 00:00:00 2001
From: Anthony Wang
Date: Tue, 22 Feb 2022 16:58:19 -0600
Subject: Add new transformers bot script and move old one to bot_lstm.py

---
 bot.py      | 38 ++++++++++++++++----------------------
 bot_lstm.py | 37 +++++++++++++++++++++++++++++++++++++
 2 files changed, 53 insertions(+), 22 deletions(-)
 create mode 100644 bot_lstm.py

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()
 
 
-mastodon = Mastodon(
-    access_token=args.token,
-    api_base_url='https://social.exozy.me/'
-)
+tokenizer = AutoTokenizer.from_pretrained('distilgpt2')
+model = AutoModelForCausalLM.from_pretrained(args.model)
 
 
-dataset = Dataset(args.input, 32)
-device = torch.device(args.device)
-model = torch.load(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)
 
 
-text = predict(device, model, args.text)
-print(text)
-# mastodon.status_post(text)
+# Post it to Mastodon
+mastodon = Mastodon(
+    access_token=args.token,
+    api_base_url='https://social.exozy.me/'
+)
+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)
-- 
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