Update all-types-of-transformers.md

all-types-of-transformers.md

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 Perfect ✅ Here’s a ready-to-use table of Hugging Face Transformers models for different data types, with their exact model IDs you can load directly.
 
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+| Data Type      | Transformer / Model           | Generative?            | Discriminative? | Extra Components Needed for Generation                        |
+| -------------- | ----------------------------- | ---------------------- | --------------- | ------------------------------------------------------------- |
+| **Text**       | GPT, T5                       | ✅ Yes                  | ⚪ Optional      | None for GPT/T5; just fine-tune on text generation task       |
+|                | BERT                          | ⚪ No                   | ✅ Yes           | Add decoder head or use in masked LM setup for generation     |
+| **Image**      | ViT                           | ⚪ No                   | ✅ Yes           | Generative decoder (e.g., UNet in diffusion models)           |
+|                | Stable Diffusion (ViT + UNet) | ✅ Yes                  | ⚪ Optional      | Pretrained pipeline handles generation                        |
+| **Audio**      | SpeechT5                      | ✅ Yes                  | ⚪ Optional      | Vocoder for waveform generation                               |
+|                | MusicLM                       | ✅ Yes                  | ⚪ Optional      | Input embeddings + autoregressive decoder for music           |
+| **Video**      | TimeSformer                   | ⚪ No                   | ✅ Yes           | Decoder for video generation (frame synthesis)                |
+|                | VideoMAE                      | ⚪ No                   | ✅ Yes           | Decoder to reconstruct/generated frames                       |
+| **Multimodal** | CLIP                          | ⚪ No                   | ✅ Yes           | Use with generative decoder (e.g., VQGAN + CLIP or diffusion) |
+|                | BLIP                          | ✅ Yes (for captioning) | ✅ Yes           | Use decoder for text generation or VQA output                 |
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 ## 🔹 Hugging Face Transformer Models by Data Type
 | Data Type                           | Model Name                  | Hugging Face ID                               |
 | ----------------------------------- | --------------------------- | --------------------------------------------- |