Upload BLIP HyperModulator v1.0.0 - 2025-08-29 02:09

README.md

@@ -32,8 +32,8 @@ from blip_hyper_modulator import BlipHyperModulator
 from sentence_transformers import SentenceTransformer
 
 # Load base BLIP model
-blip_model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
-processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
+blip_model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-large")
+processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-large")
 
 # Load hypermodulator
 hypermodulator = BlipHyperModulator.from_pretrained("path/to/model", blip_model)
@@ -51,7 +51,7 @@ lora_weights = hypermodulator.generate_lora_weights(
 
 ## Model Details
 
-- **Base Model**: Salesforce/blip-image-captioning-base
+- **Base Model**: Salesforce/blip-image-captioning-large
 - **Created**: 2025-08-29
 - **Version**: 1.0.0
 - **Framework**: PyTorch

model_metadata.json

@@ -1,7 +1,7 @@
 {
   "model_name": "BLIP HyperModulator",
   "version": "1.0.0",
-  "created_date": "2025-08-29T01:24:43.252168",
+  "created_date": "2025-08-29T02:09:41.769218",
   "description": "Enhanced hypernetwork for generating LoRA adapters for BLIP image captioning models",
   "features": {
     "cross_attention": true,