Reuse files from HF model repo

app.py

@@ -5,36 +5,19 @@ from rapgpt.config import Config
 from rapgpt.encoder import Encoder
 from rapgpt.model import HFHubTransformerModel
 import gradio as gr
+from huggingface_hub import hf_hub_download
 
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser(
-        description="Convert and push locally trained and saved model to HF Hub"
-    )
-
-    parser.add_argument(
-        "--config-file",
-        default="configs/config.toml",
-        help="Path to config file used for training.",
-    )
-    parser.add_argument(
-        "--artists-tokens",
-        default="checkpoints/fiery-spaceship-65/artists_tokens.txt",
-        help="Path to artists/tokens hashmap file generated in training.",
-    )
-    parser.add_argument(
-        "--checkpoint",
-        default="checkpoints/fiery-spaceship-65/model.pt",
-        help="Path to disk checkpoint of model.",
-    )
 
-    args = parser.parse_args()
+    artists_tokens = hf_hub_download(repo_id="hugojarkoff/rapgpt", filename="artists_tokens.txt", repo_type="model")
+    config_file = hf_hub_download(repo_id="hugojarkoff/rapgpt", filename="config.toml", repo_type="model")
 
-    with open(args.artists_tokens, "r") as f:
+    with open(artists_tokens, "r") as f:
         artists_tokens = {
             line.split(":")[0]: int(line.split(":")[1].rstrip("\n")) for line in f
         }
 
-    config = Config.load_from_toml(args.config_file)
+    config = Config.load_from_toml(config_file)
     encoder = Encoder(config=config)
     model = HFHubTransformerModel.from_pretrained("hugojarkoff/rapgpt")