feat: upload installed model

.gitignore

@@ -1,2 +1 @@
-artifacts/
 wandb/

artifacts/model-ql03493w:v3/model.ckpt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d182f833fd1de144a5d6346891697597362fbca2c8198b9baa71690cb014ff80
+size 2583633897

model.py

@@ -88,17 +88,17 @@ class ImageCaptioner(pl.LightningModule):
 
         return out
 
-@st.cache_resource
-def download_trained_model():
-    wandb.init(anonymous="must")
+# @st.cache_resource
+# def download_trained_model():
+#     wandb.init(anonymous="must")
 
-    api = wandb.Api()
-    artifact = api.artifact('hungchiehwu/CLIP-L14_GPT/model-ql03493w:v3')
-    artifact_dir = artifact.download()
+#     api = wandb.Api()
+#     artifact = api.artifact('hungchiehwu/CLIP-L14_GPT/model-ql03493w:v3')
+#     artifact_dir = artifact.download()
 
-    wandb.finish()
+#     wandb.finish()
 
-    return artifact_dir
+#     return artifact_dir
 
 @st.cache_resource
 def load_clip_model():
@@ -120,7 +120,7 @@ def load_gpt_model():
 def load_model():
 
     # # Load fine-tuned model from wandb
-    artifact_dir = download_trained_model()
+    artifact_dir = "./artifacts/model-ql03493w:v3"
     PATH = f"{artifact_dir[2:]}/model.ckpt"
 
     # Load pretrained GPT, CLIP model from OpenAI