ajout de vocab.pkl et remove de model

.gitattributes

@@ -1,2 +1 @@
 *.pt filter=lfs diff=lfs merge=lfs -text
-*.pkl filter=lfs diff=lfs merge=lfs -text

src/inference.py

@@ -34,13 +34,11 @@ def inferenceAPI(text: str) -> str:
     decoder.to(device)
 
     # On instancie le modèle
-    model = AutoModel.from_pretrained("EveSa/SummaryProject-LSTM", revision="main")
-    model = AutoModel.PretrainedConfig()
     model = EncoderDecoderModel(encoder, decoder, vectoriser, device)
 
-    model.load_state_dict(torch.load("model/model.pt", map_location=device))
-    model.eval()
-    model.to(device)
+    # model.load_state_dict(torch.load("model/model.pt", map_location=device))
+    # model.eval()
+    # model.to(device)
 
     # On vectorise le texte
     source = vectoriser.encode(text)

src/train.py

@@ -194,7 +194,7 @@ if __name__ == "__main__":
 
     torch.save(trained_classifier.state_dict(), "model/model.pt")
     vectoriser.save("model/vocab.pkl")
-    trained_classifier.config.to_json_file("config.json")
+    trained_classifier.push_to_hub("SummaryProject-LSTM")
 
     print(f"test summary : {vectoriser.decode(dev_dataset[6][1])}")
     print(