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| Leader | Take, then tweak |
|---|---|
| Anthropic | No GGUF. We keep the honesty they apply to API vs weights. |
| NVIDIA | TensorRT-LLM is their derived path. GGUF is ours. Same idea, smaller church. |
| Unsloth | Unsloth's GGUF export, labeled derived. |
szl-holdings/szl-serveQwen/Qwen2.5-1.5B-Instruct |
| License | apache-2.0 |
| Parameters | 1.5B |
| Hardware | Runs CPU-only via GGUF Q4_K_M (~0.99 GB); GPU optional |
| One command | ollama run hf.co/SZLHOLDINGS/SZL-Khipu-1.5B-GGUF:Q4_K_M || File | Bits | Size | Uploaded-byte SHA-256 (Hub LFS OID) | Use when |
|---|---|---|---|---|
| SZL-Khipu-1.5B-Q4_K_M.gguf | 4-bit | 0.99 GB | 13c1a1993063e1dff92f7413ccf48eaca6d48efc8801ae9af35961ae3396623a | Default - best size/quality balance |
| SZL-Khipu-1.5B-Q5_K_M.gguf | 5-bit | 1.13 GB | 3bf460ac163c5dc952c273999c38a41349e3e6d666e4b713aed22c996860fd4c | More quality headroom |
| SZL-Khipu-1.5B-Q8_0.gguf | 8-bit | 1.65 GB | 6aff1087f64631679f4cdf032613aee6911dbde38cd3bac6b81bf63741a56f0d | Near-lossless CPU inference |
| SZL-Khipu-1.5B-F16.gguf | 16-bit | 3.09 GB | 2348ee342efe639e100f3fb31a3dc11b8c12d8c43ecfe45e18041b9f94c71a12 | Reference / requantizing |
ollama run hf.co/SZLHOLDINGS/SZL-Khipu-1.5B-GGUF:Q4_K_Mllama-cli -hf SZLHOLDINGS/SZL-Khipu-1.5B-GGUF:Q4_K_M -p "Navigate: which receipt signed decision d-42?"SZLHOLDINGS/SZL-Khipu-1.5B-GGUF, pick Q4_K_M.{query, candidates:[{nodeId, nodeKind, label, note}]}
— handles only, never node content — and the model returns a single JSON plan
(decision=NAVIGATE citing offered handles, or decision=ABSTAIN with an
abstainReason) per khipu.schema.json. The full contract and expected output shape
live on the BrainNavigator card.1# The owner-signed receipts travel with the weights:
2# training_receipt.signed.json; eval_receipt.signed.json; owner_pubkey.json
3# They are Ed25519 signatures over canonical JSON, not DSSE envelopes.
4# Verify them offline against the repo-declared public key before use.convert_hf_to_gguf.py -> llama-quantize (F16 -> Q4_K_M / Q5_K_M / Q8_0), 2026-07-15. Quantization changes numerics; the signed evaluation receipt covers the pre-quantized BrainNavigator evaluation artifact described by that receipt, not any GGUF. The LFS hashes above bind the exact uploaded GGUF bytes. No post-quantization quality evaluation or independent benchmark is claimed.