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indoSBERT-large
denaya基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗albedo-qwen3.6-35b-king-CXXVIII
dendriteholdings基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Ingot-genesis-27B-FP8
dendriteholdings基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Ingot-genesis-27B-Q2
dendriteholdingsThe genesis model of Ingot's **27B-Q2** competition: the first king that every q2 submission is scored against. This is an unmodified copy of `Ternary-Bonsai-2-27B-PQ2_0.gguf` from prism-ml/Ternary-Bonsai-2-27B-gguf at revision `b072e1d3b35a0a630cece372c2127528e0994386`, renamed to `Ingot-genesis-27B-Q2.gguf`. Created using Bonsai by Prism ML. PQ2_0 needs the PrismML llama.cpp fork; stock llama.cpp does not load it. Ingot evaluates with the fork at tag `prism-b10777-e3de715`.
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View details ↗Ingot-I-27B-Q2
dendriteholdingsA public mirror of a model that won on Ingot, a Bittensor subnet where miners quantize a fixed teacher model and the validator crowns the copy that stays closest to it. It is Prism ML's Ternary Bonsai 2 27B, refined: the same ternary codes, with the per-block scales and the norm weights re-tuned by the miner to bring it closer to Qwen3.8-27B. The weights are the miner's upload, byte for byte. Credit belongs to the miner, and to Prism ML for Bonsai 2.
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View details ↗Ingot-II-27B-Q2
dendriteholdingsA public mirror of a model that won on Ingot, a Bittensor subnet where miners quantize a fixed teacher model and the validator crowns the copy that stays closest to it. It is Prism ML's Ternary Bonsai 2 27B, refined: the same ternary codes, with the per-block scales and the norm weights re-tuned by the miner to bring it closer to Qwen3.8-27B. The weights are the miner's upload, byte for byte. Credit belongs to the miner, and to Prism ML for Bonsai 2.
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View details ↗Ingot-III-27B-FP8
dendriteholdings基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Ingot-III-27B-Q2
dendriteholdingsA public mirror of a model that won on Ingot, a Bittensor subnet where miners quantize a fixed teacher model and the validator crowns the copy that stays closest to it. It is Prism ML's Ternary Bonsai 2 27B, refined: the same ternary codes, with the per-block scales and the norm weights re-tuned by the miner to bring it closer to Qwen3.8-27B. The weights are the miner's upload, byte for byte. Credit belongs to the miner, and to Prism ML for Bonsai 2.
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View details ↗Ingot-IV-27B-FP8
dendriteholdings基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Ingot-IV-27B-Q2
dendriteholdingsA public mirror of a model that won on Ingot, a Bittensor subnet where miners quantize a fixed teacher model and the validator crowns the copy that stays closest to it. It is Prism ML's Ternary Bonsai 2 27B, refined: the same ternary codes, with the per-block scales and the norm weights re-tuned by the miner to bring it closer to Qwen3.8-27B. The weights are the miner's upload, byte for byte (`Ingot-IV-27B-PQ2_0.gguf`); `Ingot-IV-27B-PTQ1_0.gguf` repacks them losslessly at 1.75 bits per weight. Credit belongs to the miner, and to Prism ML for Bonsai 2.
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View details ↗Ingot-IX-27B-Q2
dendriteholdingsA public mirror of a model that won on Ingot, a Bittensor subnet where miners quantize a fixed teacher model and the validator crowns the copy that stays closest to it. It is Prism ML's Ternary Bonsai 2 27B, refined: the same ternary codes, with the per-block scales and the norm weights re-tuned by the miner to bring it closer to Qwen3.8-27B. The weights are the miner's upload, byte for byte. Credit belongs to the miner, and to Prism ML for Bonsai 2.
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View details ↗Ingot-V-27B-FP8
dendriteholdings基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Ingot-V-27B-Q2
dendriteholdingsA public mirror of a model that won on Ingot, a Bittensor subnet where miners quantize a fixed teacher model and the validator crowns the copy that stays closest to it. It is Prism ML's Ternary Bonsai 2 27B, refined: the same ternary codes, with the per-block scales and the norm weights re-tuned by the miner to bring it closer to Qwen3.8-27B. The weights are the miner's upload, byte for byte. Credit belongs to the miner, and to Prism ML for Bonsai 2.
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View details ↗Ingot-VI-27B-Q2
dendriteholdingsA public mirror of a model that won on Ingot, a Bittensor subnet where miners quantize a fixed teacher model and the validator crowns the copy that stays closest to it. It is Prism ML's Ternary Bonsai 2 27B, refined: the same ternary codes, with the per-block scales and the norm weights re-tuned by the miner to bring it closer to Qwen3.8-27B. The weights are the miner's upload, byte for byte. Credit belongs to the miner, and to Prism ML for Bonsai 2.
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View details ↗Ingot-VII-27B-Q2
dendriteholdingsA public mirror of a model that won on Ingot, a Bittensor subnet where miners quantize a fixed teacher model and the validator crowns the copy that stays closest to it. It is Prism ML's Ternary Bonsai 2 27B, refined: the same ternary codes, with the per-block scales and the norm weights re-tuned by the miner to bring it closer to Qwen3.8-27B. The weights are the miner's upload, byte for byte. Credit belongs to the miner, and to Prism ML for Bonsai 2.
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View details ↗Ingot-VIII-27B-Q2
dendriteholdingsA public mirror of a model that won on Ingot, a Bittensor subnet where miners quantize a fixed teacher model and the validator crowns the copy that stays closest to it. It is Prism ML's Ternary Bonsai 2 27B, refined: the same ternary codes, with the per-block scales and the norm weights re-tuned by the miner to bring it closer to Qwen3.8-27B. The weights are the miner's upload, byte for byte. Credit belongs to the miner, and to Prism ML for Bonsai 2.
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View details ↗Ingot-X-27B-Q2
dendriteholdingsA public mirror of a model that won on Ingot, a Bittensor subnet where miners quantize a fixed teacher model and the validator crowns the copy that stays closest to it. It is Prism ML's Ternary Bonsai 2 27B, refined: the same ternary codes, with the per-block scales and the norm weights re-tuned by the miner to bring it closer to Qwen3.8-27B. The weights are the miner's upload, byte for byte. Credit belongs to the miner, and to Prism ML for Bonsai 2.
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View details ↗Ingot-XI-27B-Q2
dendriteholdingsA public mirror of a model that won on Ingot, a Bittensor subnet where miners quantize a fixed teacher model and the validator crowns the copy that stays closest to it. It is Prism ML's Ternary Bonsai 2 27B, refined: the same ternary codes, with the per-block scales and the norm weights re-tuned by the miner to bring it closer to Qwen3.8-27B. The weights are the miner's upload, byte for byte. Credit belongs to the miner, and to Prism ML for Bonsai 2.
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View details ↗Ingot-XII-27B-Q2
dendriteholdingsA public mirror of a model that won on Ingot, a Bittensor subnet where miners quantize a fixed teacher model and the validator crowns the copy that stays closest to it. It is Prism ML's Ternary Bonsai 2 27B, refined: the same ternary codes, with the per-block scales and the norm weights re-tuned by the miner to bring it closer to Qwen3.8-27B. The weights are the miner's upload, byte for byte (`Ingot-XII-27B-PQ2_0.gguf`); `Ingot-XII-27B-PTQ1_0.gguf` repacks them losslessly at 1.75 bits per weight. Credit belongs to the miner, and to Prism ML for Bonsai 2.
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View details ↗Ingot-XIII-27B-Q2
dendriteholdingsA public mirror of a model that won on Ingot, a Bittensor subnet where miners quantize a fixed teacher model and the validator crowns the copy that stays closest to it. It is Prism ML's Ternary Bonsai 2 27B, refined: the same ternary codes, with the per-block scales and the norm weights re-tuned by the miner to bring it closer to Qwen3.8-27B. The weights are the miner's upload, byte for byte (`Ingot-XIII-27B-PQ2_0.gguf`); `Ingot-XIII-27B-PTQ1_0.gguf` repacks them losslessly at 1.75 bits per weight. Credit belongs to the miner, and to Prism ML for Bonsai 2.
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View details ↗Ingot-XIV-27B-Q2
dendriteholdings基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Ingot-XV-27B-Q2
dendriteholdingsA public mirror of a model that won on Ingot, a Bittensor subnet where miners quantize a fixed teacher model and the validator crowns the copy that stays closest to it. It is Prism ML's Ternary Bonsai 2 27B, refined: the same ternary codes, with the per-block scales and the norm weights re-tuned by the miner to bring it closer to Qwen3.8-27B. The weights are the miner's upload, byte for byte (`Ingot-XV-27B-PQ2_0.gguf`); `Ingot-XV-27B-PTQ1_0.gguf` repacks them losslessly at 1.75 bits per weight. Credit belongs to the miner, and to Prism ML for Bonsai 2.
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View details ↗Ingot-XVI-27B-Q2
dendriteholdingsA public mirror of a model that won on Ingot, a Bittensor subnet where miners quantize a fixed teacher model and the validator crowns the copy that stays closest to it. It is Prism ML's Ternary Bonsai 2 27B, refined: the same ternary codes, with the rest of its weights re-tuned by the miner to bring it closer to Qwen3.8-27B. The weights are the miner's upload, byte for byte (`Ingot-XVI-27B-PQ2_0.gguf`); `Ingot-XVI-27B-PTQ1_0.gguf` repacks them losslessly at 1.75 bits per weight. Credit belongs to the miner, and to Prism ML for Bonsai 2.
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