Upload app.py with huggingface_hub

app.py

@@ -2,11 +2,26 @@ import streamlit as st
 from PIL import Image
 import numpy as np
 
+import open_clip
 
-modelpath = '20241204-ams-no-env-open_clip_ViT-H-14-378-quickgelu.npz'
+#from transformers import CLIPProcessor, CLIPModel
 
-model = np.load(modelpath)
-st.write(model['walkability_vecs'].shape)
+knnpath = '20241204-ams-no-env-open_clip_ViT-H-14-378-quickgelu.npz'
+clip_model_name = 'ViT-H-14-378-quickgelu'
+
+#model, preprocess = open_clip.create_model_from_pretrained('hf-hub:laion/CLIP-ViT-g-14-laion2B-s12B-b42K')
+#tokenizer = open_clip.get_tokenizer('hf-hub:laion/CLIP-ViT-g-14-laion2B-s12B-b42K')
+
+model, preprocess = open_clip.create_model_from_pretrained(clip_model_name)
+tokenizer = open_clip.get_tokenizer(clip_model_name)
+
+st.write(model)
+#clip_model = CLIPModel.from_pretrained()
+#clip_processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")
+
+
+knn = np.load(modelpath)
+st.write(knn['walkability_vecs'].shape)
 
 file = st.file_uploader('Upload An Image')