updated with correct adapter use

README.md

@@ -44,18 +44,49 @@ Install the required dependencies:
 pip install transformers torch numpy pandas anarci
 ```
 
-## 🚀 Loading Models
+## 🚀 Loading Models from Hugging Face Hub
 
+### Method 1: Load Model and Tokenizer, then Import Adapter
 ```python
+import sys
+import os
 from transformers import AutoModel, AutoTokenizer
-from adapter import AbLang2PairedHuggingFaceAdapter
+from transformers.utils import cached_file
 
-# AbLang2
+# Load model and tokenizer from Hugging Face Hub
 model = AutoModel.from_pretrained("hemantn/ablang2", trust_remote_code=True)
 tokenizer = AutoTokenizer.from_pretrained("hemantn/ablang2", trust_remote_code=True)
+
+# Find the cached model directory and import adapter
+adapter_path = cached_file("hemantn/ablang2", "adapter.py")
+cached_model_dir = os.path.dirname(adapter_path)
+sys.path.insert(0, cached_model_dir)
+
+# Import and create the adapter
+from adapter import AbLang2PairedHuggingFaceAdapter
 ablang = AbLang2PairedHuggingFaceAdapter(model=model, tokenizer=tokenizer)
 ```
 
+### Method 2: Using importlib (Alternative)
+```python
+import importlib.util
+from transformers import AutoModel, AutoTokenizer
+from transformers.utils import cached_file
+
+# Load model and tokenizer
+model = AutoModel.from_pretrained("hemantn/ablang2", trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained("hemantn/ablang2", trust_remote_code=True)
+
+# Load adapter dynamically
+adapter_path = cached_file("hemantn/ablang2", "adapter.py")
+spec = importlib.util.spec_from_file_location("adapter", adapter_path)
+adapter_module = importlib.util.module_from_spec(spec)
+spec.loader.exec_module(adapter_module)
+
+# Create the adapter
+ablang = adapter_module.AbLang2PairedHuggingFaceAdapter(model=model, tokenizer=tokenizer)
+```
+
 **Note**: Models automatically use GPU when available, otherwise fall back to CPU.
 
 ## ⚙️ Available Utilities
@@ -70,30 +101,39 @@ ablang = AbLang2PairedHuggingFaceAdapter(model=model, tokenizer=tokenizer)
 
 ## 💡 Examples
 
-### 🔗 AbLang2 (Paired Sequences)
+### 🔗 AbLang2 (Paired Sequences) - Restore Example
 ```python
+import sys
+import os
 from transformers import AutoModel, AutoTokenizer
+from transformers.utils import cached_file
+
+# 1. Load model and tokenizer from Hugging Face Hub
+model = AutoModel.from_pretrained("hemantn/ablang2", trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained("hemantn/ablang2", trust_remote_code=True)
+
+# 2. Import adapter
+adapter_path = cached_file("hemantn/ablang2", "adapter.py")
+cached_model_dir = os.path.dirname(adapter_path)
+sys.path.insert(0, cached_model_dir)
 from adapter import AbLang2PairedHuggingFaceAdapter
 
-# Load model
-model = AutoModel.from_pretrained("your-username/ablang2", trust_remote_code=True)
-tokenizer = AutoTokenizer.from_pretrained("your-username/ablang2", trust_remote_code=True)
+# 3. Create adapter
 ablang = AbLang2PairedHuggingFaceAdapter(model=model, tokenizer=tokenizer)
 
-# Restore masked paired sequences
+# 4. Restore masked sequences
 masked_seqs = [
     ['EVQ***SGGEVKKPGASVKVSCRASGYTFRNYGLTWVRQAPGQGLEWMGWISAYNGNTNYAQKFQGRVTLTTDTSTSTAYMELRSLRSDDTAVYFCAR**PGHGAAFMDVWGTGTTVTVSS',
      'DIQLTQSPLSLPVTLGQPASISCRSS*SLEASDTNIYLSWFQQRPGQSPRRLIYKI*NRDSGVPDRFSGSGSGTHFTLRISRVEADDVAVYYCMQGTHWPPAFGQGTKVDIK']
 ]
 restored = ablang(masked_seqs, mode='restore')
+print(f"Restored sequences: {restored}")
 ```
 
 ## 📚 Detailed Usage
 
-For comprehensive examples and detailed usage instructions, see:
-- [`test_ablang2_HF_implementation.ipynb`](test_ablang2_HF_implementation.ipynb)
-
-This notebook demonstrates all utilities with real examples, including alignment features and advanced usage patterns.
+For comprehensive examples of all utilities (seqcoding, rescoding, likelihood, probability, pseudo_log_likelihood, confidence, and more), see:
+- **[`test_ablang2_HF_implementation.ipynb`](test_ablang2_HF_implementation.ipynb)** - Complete notebook with all utilities and advanced usage patterns
 
 ## 📖 Citation