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--- |
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license: apache-2.0 |
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language: |
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- en |
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base_model: |
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- katanemo/Arch-Router-1.5B |
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pipeline_tag: text-generation |
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library_name: transformers |
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tags: |
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- text-generation-inference |
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--- |
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# **Arch-Router-1.5B** |
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> 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. |
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## Model Files |
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| File Name | Size | Type | Description | |
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|-----------|------|------|-------------| |
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| Arch-Router-1.5B.Q2_K.gguf | 676 MB | Model | Q2_K quantized model (smallest) | |
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| Arch-Router-1.5B.Q3_K_S.gguf | 761 MB | Model | Q3_K_S quantized model | |
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| Arch-Router-1.5B.Q3_K_M.gguf | 824 MB | Model | Q3_K_M quantized model | |
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| Arch-Router-1.5B.Q3_K_L.gguf | 880 MB | Model | Q3_K_L quantized model | |
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| Arch-Router-1.5B.Q4_K_S.gguf | 940 MB | Model | Q4_K_S quantized model | |
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| Arch-Router-1.5B.Q4_K_M.gguf | 986 MB | Model | Q4_K_M quantized model | |
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| Arch-Router-1.5B.Q5_K_S.gguf | 1.1 GB | Model | Q5_K_S quantized model | |
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| Arch-Router-1.5B.Q5_K_M.gguf | 1.13 GB | Model | Q5_K_M quantized model | |
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| Arch-Router-1.5B.Q6_K.gguf | 1.27 GB | Model | Q6_K quantized model | |
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| Arch-Router-1.5B.Q8_0.gguf | 1.65 GB | Model | Q8_0 quantized model | |
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| Arch-Router-1.5B.BF16.gguf | 3.09 GB | Model | BF16 precision model | |
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| Arch-Router-1.5B.F16.gguf | 3.09 GB | Model | F16 precision model | |
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| Arch-Router-1.5B.F32.gguf | 6.18 GB | Model | F32 full precision model (largest) | |
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| .gitattributes | 2.49 kB | Config | Git LFS configuration | |
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| config.json | 31 Bytes | Config | Model configuration | |
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| README.md | 173 Bytes | Documentation | Repository documentation | |
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## Quants Usage |
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(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) |
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Here is a handy graph by ikawrakow comparing some lower-quality quant |
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types (lower is better): |
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