valendra/Ternary-Bonsai-2-27B-safetensors
text-generation model by valendra
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Model card & documentation
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Experimental SafeTensors checkpoint for the Ternary Bonsai 2 27B text model. This repository contains the converted model weights together with the tokenizer, chat template, and configuration required by a compatible runtime. The quantization configuration uses an automatic ternary target and a normalized Sylvester-Walsh-Hadamard transform with 1024-element blocks and explicit signs. The checkpoint is not a conventional BF16 or FP16 model. This checkpoint is intended for research, runtime integration, and evaluation of ternary model inference. It requires a runtime that implements the Bonsai2ForCausalLM architecture and the bonsaiternary quantization format. The corresponding Valendra vLLM implementation is available at: Use a…
Read the full model card ↗ · Preview checked 2026-09-23T09:18:24.345Z
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Model overview
valendra/Ternary-Bonsai-2-27B-safetensors is a text-generation model repository published by valendra on Hugging Face. A library was not reported.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-generation
- Library
- Not reported
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 6,743,678,464
- Architecture
- Bonsai2ForCausalLM
- License
- Not reported — check the model card
- Access
- Not gated by Hugging Face
- Created
- 2026-09-23T06:10:30.000Z
- Last modified
- 2026-09-23T06:24:40.000Z
Compatibility and lineage
Language coverage was not reported.
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-23T06:37:25.545Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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