Update README.md

README.md

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 # **Arch-Router-1.5B**
 
-> Arch-Router-1.5B introduces a preference-aligned routing framework that guides model selection by matching queries to user-defined domains (e.g., travel) or action types (e.g., image editing) -- offering a practical mechanism to encode preferences in routing decisions. Specifically, we introduce Arch-Router, a compact 1.5B model that learns to map queries to domain-action preferences for model routing decisions. Experiments on conversational datasets demonstrate that our approach achieves state-of-the-art (SOTA) results in matching queries with human preferences, outperforming top proprietary models. 
+> Arch-Router-1.5B introduces a preference-aligned routing framework that guides model selection by matching queries to user-defined domains (e.g., travel) or action types (e.g., image editing) -- offering a practical mechanism to encode preferences in routing decisions. Specifically, we introduce Arch-Router, a compact 1.5B model that learns to map queries to domain-action preferences for model routing decisions. Experiments on conversational datasets demonstrate that our approach achieves state-of-the-art (SOTA) results in matching queries with human preferences, outperforming top proprietary models.
+
+## Model Files
+
+| File Name | Size | Type | Description |
+|-----------|------|------|-------------|
+| Arch-Router-1.5B.Q2_K.gguf | 676 MB | Model | Q2_K quantized model (smallest) |
+| Arch-Router-1.5B.Q3_K_S.gguf | 761 MB | Model | Q3_K_S quantized model |
+| Arch-Router-1.5B.Q3_K_M.gguf | 824 MB | Model | Q3_K_M quantized model |
+| Arch-Router-1.5B.Q3_K_L.gguf | 880 MB | Model | Q3_K_L quantized model |
+| Arch-Router-1.5B.Q4_K_S.gguf | 940 MB | Model | Q4_K_S quantized model |
+| Arch-Router-1.5B.Q4_K_M.gguf | 986 MB | Model | Q4_K_M quantized model |
+| Arch-Router-1.5B.Q5_K_S.gguf | 1.1 GB | Model | Q5_K_S quantized model |
+| Arch-Router-1.5B.Q5_K_M.gguf | 1.13 GB | Model | Q5_K_M quantized model |
+| Arch-Router-1.5B.Q6_K.gguf | 1.27 GB | Model | Q6_K quantized model |
+| Arch-Router-1.5B.Q8_0.gguf | 1.65 GB | Model | Q8_0 quantized model |
+| Arch-Router-1.5B.BF16.gguf | 3.09 GB | Model | BF16 precision model |
+| Arch-Router-1.5B.F16.gguf | 3.09 GB | Model | F16 precision model |
+| Arch-Router-1.5B.F32.gguf | 6.18 GB | Model | F32 full precision model (largest) |
+| .gitattributes | 2.49 kB | Config | Git LFS configuration |
+| config.json | 31 Bytes | Config | Model configuration |
+| README.md | 173 Bytes | Documentation | Repository documentation |
+
+## Quants Usage 
+
+(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
+
+Here is a handy graph by ikawrakow comparing some lower-quality quant
+types (lower is better):
+
+![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)