Delete push-model.py

push-model.py

@@ -1,169 +0,0 @@
-import os
-from typing import Optional
-
-from huggingface_hub import HfApi, create_repo
-from transformers import AutoConfig, AutoModelForCausalLM, AutoProcessor
-
-
-class SpecVisionModelRegistration:
-    """
-    Handles the registration and pushing of SpecVision model to Hugging Face Hub.
-    """
-    
-    def __init__(self, 
-                 model_path: str,
-                 repo_name: str,
-                 organization: Optional[str] = None,
-                 token: Optional[str] = None):
-        """
-        Initialize the registration handler.
-        
-        Args:
-            model_path: Local path to your model files
-            repo_name: Name for the Hugging Face repository
-            organization: Optional organization name on Hugging Face
-            token: Hugging Face API token
-        """
-        self.model_path = model_path
-        self.repo_name = repo_name
-        self.organization = organization
-        self.token = token or os.getenv("HF_TOKEN")
-        
-        if not self.token:
-            raise ValueError("Please provide a Hugging Face token either directly or via HF_TOKEN environment variable")
-            
-        self.api = HfApi()
-        
-    def register_model_components(self):
-        """
-        Register the SpecVision model architecture components with the transformers library.
-        """
-        # Import your custom model classes
-        from configuration_spec_vision import SpecVisionConfig
-        from modeling_spec_vision import SpecVisionForCausalLM
-        from processing_spec_vision import SpecVisionProcessor
-
-        # Register the model architecture
-        AutoConfig.register("spec_vision", SpecVisionConfig)
-        AutoModelForCausalLM.register(SpecVisionConfig, SpecVisionForCausalLM)
-        AutoProcessor.register(SpecVisionConfig, SpecVisionProcessor)
-        
-        print("✓ Successfully registered SpecVision model architecture")
-        
-    def create_huggingface_repo(self):
-        """
-        Create a new repository on the Hugging Face Hub.
-        """
-        repo_id = f"{self.organization}/{self.repo_name}" if self.organization else self.repo_name
-        
-        try:
-            create_repo(
-                repo_id,
-                token=self.token,
-                private=False,
-                exist_ok=True
-            )
-            print(f"✓ Created/accessed repository: {repo_id}")
-            return repo_id
-        except Exception as e:
-            raise Exception(f"Failed to create repository: {str(e)}")
-            
-    def update_model_card(self):
-        """
-        Create or update the model card (README.md) with necessary information.
-        """
-        model_card = f"""---
-language: en
-tags:
-- spec-vision
-- vision-language-model
-- transformers
-license: apache-2.0
----
-
-# SpecVision Model
-
-This is the SpecVision model, a vision-language model based on the transformers architecture.
-
-## Model Description
-
-SpecVision is designed for vision-language tasks, combining visual and textual understanding capabilities.
-
-## Usage
-
-```python
-from transformers import AutoConfig, AutoModelForCausalLM, AutoProcessor
-
-# Load the model and processor
-model = AutoModelForCausalLM.from_pretrained("{self.repo_name}")
-processor = AutoProcessor.from_pretrained("{self.repo_name}")
-
-# Process inputs
-inputs = processor(images=image, text=text, return_tensors="pt")
-outputs = model(**inputs)
-```
-
-## Training and Evaluation
-
-[Add your training and evaluation details here]
-
-## Limitations and Biases
-
-[Add any known limitations and biases here]
-"""
-        
-        with open(os.path.join(self.model_path, "README.md"), "w") as f:
-            f.write(model_card)
-            
-        print("✓ Created/updated model card")
-        
-    def push_to_hub(self):
-        """
-        Push the model, configurations, and related files to Hugging Face Hub.
-        """
-        repo_id = self.create_huggingface_repo()
-        
-        # Update the model card first
-        self.update_model_card()
-        
-        # Create a dictionary of files to upload
-        files_to_upload = {}
-        for filename in os.listdir(self.model_path):
-            if filename.endswith(('.json', '.py', '.md', '.txt', '.safetensors')):
-                filepath = os.path.join(self.model_path, filename)
-                files_to_upload[filename] = filepath
-        
-        # Upload all files
-        for filename, filepath in files_to_upload.items():
-            self.api.upload_file(
-                path_or_fileobj=filepath,
-                path_in_repo=filename,
-                repo_id=repo_id,
-                token=self.token
-            )
-            print(f"✓ Uploaded {filename}")
-            
-        print(f"\nModel successfully pushed to https://huggingface.co/{repo_id}")
-
-def main():
-    """
-    Main function to execute the registration and push process.
-    """
-    # You can set your HF_TOKEN as an environment variable or pass it directly
-    TOKEN = os.getenv("HF_TOKEN")  # or "your_token_here"
-    
-    registration = SpecVisionModelRegistration(
-        model_path="./",  # Assuming you're running from the model directory
-        repo_name="Spec-4B-Vision-V1",  # Change this to your desired repo name
-        organization="SVECTOR-CORPORATION",  # Your organization name
-        token=TOKEN
-    )
-    
-    # Register the model architecture
-    registration.register_model_components()
-    
-    # Push everything to the Hub
-    registration.push_to_hub()
-    
-if __name__ == "__main__":
-    main()