ewchampion/Ternary-Bonsai-1.7B-TQ2_0-GGUF overview
Ternary Bonsai 1.7B TQ2 0 GGUF Requantized from prism ml/Ternary Bonsai 1.7B gguf https://huggingface.co/prism ml/Ternary Bonsai 1.7B gguf 's F16 baseline to G…
Runs locally from ~595.6 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Ternary-Bonsai-1.7B-TQ2_0.gguf | GGUF | GGUF | 595.6 MB | Download |
Model Details
| Model ID | ewchampion/Ternary-Bonsai-1.7B-TQ2_0-GGUF |
|---|---|
| Author | ewchampion |
| Pipeline | — |
| License | apache-2.0 |
| Base model | prism-ml/Ternary-Bonsai-1.7B-gguf |
| Last modified | 2026-07-09T16:50:53.000Z |
Model README
---
license: apache-2.0
base_model: prism-ml/Ternary-Bonsai-1.7B-gguf
---
Ternary-Bonsai-1.7B-TQ2_0-GGUF
Requantized from prism-ml/Ternary-Bonsai-1.7B-gguf's F16 baseline to GGML's native TQ2_0 ternary type (~2.06 bits/weight), using stock llama.cpp (tag b9498) — not PrismML's custom fork/packing.
Sanity-checked via llama-server's OpenAI-compatible endpoint on CPU (Metal has no TQ1_0/TQ2_0 matmul kernels at this llama.cpp version — this model must run with -ngl 0 / CPU-only until upstream adds Metal support):
- Chat coherence: pass ("What is the capital of France?" -> "Paris.")
- Native tool-calling (Qwen3
<tool_call>format): pass, clean structuredtool_callsoutput.
License: Apache 2.0 (carried over from base model).
Run ewchampion/Ternary-Bonsai-1.7B-TQ2_0-GGUF with guIDE
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Source: Hugging Face · Compare models