docs: remove AWQ variants from family table (AWQ lane paused, repos private)

README.md

@@ -115,13 +115,11 @@ This model requires approximately 31 GB of unified memory. Recommended hardware:
 
 ## Variants in this family
 
-(Showing 18 sibling variants under `majentik/gemma-4-31b-*`. The current variant — `RotorQuant-MLX-8bit` — is **bolded**.)
+(Showing 14 sibling variants under `majentik/gemma-4-31b-*`. The current variant — `RotorQuant-MLX-8bit` — is **bolded**.)
 
 | Variant | Runtime | Approx size | Use case |
 |---|---|---|---|
 | [RotorQuant](https://huggingface.co/majentik/gemma-4-31b-rotorquant) | runtime modifier | n/a | KV-cache root (weight-agnostic) |
-| [RotorQuant-AWQ-4bit](https://huggingface.co/majentik/gemma-4-31b-rotorquant-awq-4bit) | transformers | ~19 GB | GPU 4-bit (AutoAWQ) |
-| [RotorQuant-AWQ-8bit](https://huggingface.co/majentik/gemma-4-31b-rotorquant-awq-8bit) | transformers | ~34 GB | GPU 8-bit (AutoAWQ) |
 | [RotorQuant-GGUF-IQ4_XS](https://huggingface.co/majentik/gemma-4-31b-rotorquant-gguf-IQ4_XS) | llama.cpp | ~27 GB | Lossy 4-bit, low-RAM CPU/edge |
 | [RotorQuant-GGUF-Q2_K](https://huggingface.co/majentik/gemma-4-31b-rotorquant-gguf-Q2_K) | llama.cpp | ~19 GB | Lossy, low-RAM CPU/edge |
 | [RotorQuant-GGUF-Q3_K_M](https://huggingface.co/majentik/gemma-4-31b-rotorquant-gguf-Q3_K_M) | llama.cpp | ~24 GB | Smaller 3-bit, CPU-friendly |
@@ -132,8 +130,6 @@ This model requires approximately 31 GB of unified memory. Recommended hardware:
 | [RotorQuant-MLX-4bit](https://huggingface.co/majentik/gemma-4-31b-rotorquant-mlx-4bit) | mlx-lm | ~19 GB | Apple Silicon balanced |
 | **RotorQuant-MLX-8bit** | mlx-lm | ~37 GB | Apple Silicon reference |
 | [TurboQuant](https://huggingface.co/majentik/gemma-4-31b-turboquant) | runtime modifier | n/a | KV-cache root (weight-agnostic) |
-| [TurboQuant-AWQ-4bit](https://huggingface.co/majentik/gemma-4-31b-turboquant-awq-4bit) | transformers | ~19 GB | GPU 4-bit (AutoAWQ) |
-| [TurboQuant-AWQ-8bit](https://huggingface.co/majentik/gemma-4-31b-turboquant-awq-8bit) | transformers | ~34 GB | GPU 8-bit (AutoAWQ) |
 | [TurboQuant-MLX-2bit](https://huggingface.co/majentik/gemma-4-31b-turboquant-mlx-2bit) | mlx-lm | ~9.9 GB | Apple Silicon, smallest |
 | [TurboQuant-MLX-4bit](https://huggingface.co/majentik/gemma-4-31b-turboquant-mlx-4bit) | mlx-lm | ~19 GB | Apple Silicon balanced |
 | [TurboQuant-MLX-8bit](https://huggingface.co/majentik/gemma-4-31b-turboquant-mlx-8bit) | mlx-lm | ~37 GB | Apple Silicon reference |