i have this system i want more detailes and expand in drawing: Building the System from Scratch using pre-trained models for text, vision, and vision-language integration, incorporating an Attentive Fusion mechanism to synergize multimodal data effectively.
integrating them through the Attentive Fusion mechanism. 
o	Cross-Modal Transformer Modules are designed to enable information flow between text and image modalities, enhancing the system's ability to detect hate speech that may be expressed through either or both.
o	Sampling Blocks precede these modules to ensure that only the most relevant features are processed, optimizing both performance and computational efficiency
Example
•  
Input Submission:
o	Text: "I hate [target group] because..."
o	Image: An offensive meme related to the same target group.
•  Data Preprocessing:
o	Text: Cleaned and tokenized, resulting in embeddings.
o	Image: Resized, augmented, and embedded, resulting in patch embeddings.
o	Paired Data: Encoded via CLIP for joint representations.
•  Sampling:
o	Text Sampling Block: Selects critical tokens (e.g., offensive terms) based on attention.
o	Image Sampling Block: Selects salient patches (e.g., specific symbols or imagery) based on attention.
•  Cross-Modal Encoding:
o	Transformer Module 1: Integrates selected text embeddings to inform image feature decoding.
o	Transformer Module 2: Integrates selected image embeddings to inform text feature decoding.
•  Sequential Learning:
o	LSTM Blocks: Capture temporal dependencies in both pipelines.
•  Attentive Fusion and Classification:
o	Fusion: Combines features.
o	Classification: Determines the presence and type of hate speech.
+-----------------------------------------+
|             Data Collection             |
|  (Separate Collection for Text, Images, |
|         and Paired Image-Text Data)     |
+---------------------+-------------------+
                      |
                      v
+---------------------+-------------------+
|             Data Preprocessing          |
|  - Text Cleaning & Tokenization         |
|  - Image Resizing & Augmentation        |
|  - Paired Data Alignment & Synchronization|
+---------------------+-------------------+
                      |
                      v
+---------------------+-------------------+
|           Feature Extraction            |
|  +-------------------+----------------+ |
|  |    Text Encoder    |  Image Encoder | |
|  |   (RoBERTa)        | (EfficientNet) | |
|  +-------------------+----------------+ |
|                  |                        |
|                  v                        |
|        Vision-Language Encoder (CLIP)    |
+---------------------+-------------------+
                      |
                      v
+---------------------+-------------------+
|             Sampling Blocks             |
|  +-----------+       +-----------------+|
|  | Text      |       | Image           ||
|  | Sampling  |       | Sampling        ||
|  | Block     |       | Block           ||
|  +-----------+       +-----------------+|
|                  |                        |
|                  v                        |
|         Paired Data Sampling Block      |
+---------------------+-------------------+
                      |
                      v
+---------------------+-------------------+
|    Cross-Modal Transformer Modules      |
|  +-----------------+  +----------------+
|  | Transformer Module 1 | Transformer Module 2|
|  | (Text → Image)       | (Image → Text)      |
|  +-----------------+  +----------------+
                      |
                      v
+---------------------+-------------------+
|          LSTM Processing Pipelines       |
|  +-------------------+  +----------------+
|  | LSTM Block 1      |  | LSTM Block 2   |
|  | (Pipeline 1)      |  | (Pipeline 2)   |
|  +-------------------+  +----------------+
                      |
                      v
+---------------------+-------------------+
|           Attentive Fusion Layer        |
+---------------------+-------------------+
                      |
                      v
+---------------------+-------------------+
|           Classification Layer           |
|  - Linear Layer                         |
|  - Softmax Activation                   |
+---------------------+-------------------+
                      |
                      v
+---------------------+-------------------+
|        System Integration & Deployment   |
|  - API Development                       |
|  - Frontend Interface                    |
|  - Containerization (Docker)             |
|  - Orchestration (Kubernetes)            |
|  - Cloud Deployment                      |
|  - Monitoring & Maintenance              |
+-----------------------------------------+