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Model: Entrit/Qwen2.5-3B-trit-uniform-d3
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen2.5-3B
+tags:
+  - quantization
+  - ternary
+  - balanced-ternary
+  - tritllm
+library_name: transformers
+---
+
+# Qwen2.5-3B-trit-uniform-d3
+
+Balanced ternary quantization of [`Qwen/Qwen2.5-3B`](https://huggingface.co/Qwen/Qwen2.5-3B) at depth **d=3** (27 levels per weight, **5.05 bits per weight**).
+
+Produced with the codec from **"Balanced Ternary Post-Training Quantization for Large Language Models"** (Stentzel, 2026). See [Entrit/tritllm-codec](https://huggingface.co/Entrit/tritllm-codec) for the codec source.
+
+## Quick load
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("Entrit/Qwen2.5-3B-trit-uniform-d3")
+tokenizer = AutoTokenizer.from_pretrained("Entrit/Qwen2.5-3B-trit-uniform-d3")
+```
+
+The weights are dequantized to FP16 for stock-`transformers` compatibility. The on-disk size is therefore the same as the FP16 source. The 5.05-bpw figure refers to the *information content* of the quantized matrices and is what matters for inference on hardware that consumes the packed trit format directly (see [Entrit/tritllm-kernel](https://huggingface.co/Entrit/tritllm-kernel)).
+
+## Quantization details
+
+| Field | Value |
+|---|---|
+| Source model | [`Qwen/Qwen2.5-3B`](https://huggingface.co/Qwen/Qwen2.5-3B) |
+| Depth | d=3 (27 levels) |
+| Bits per weight | 5.05 |
+| Group size | 16 |
+| Scale codebook | 27-entry log-spaced (scale_depth=3) |
+| Method | Uniform PTQ |
+| Quantized layers | all 2D linear matrices |
+| Kept FP16 | `lm_head`, token embeddings, all `*_norm` layers |
+| Codec | tritllm v2 |
+
+## Citation
+
+```
+@article{stentzel2026ternaryptq,
+  title  = {Balanced Ternary Post-Training Quantization for Large Language Models},
+  author = {Stentzel, Eric},
+  year   = 2026,
+  note   = {Entrit Systems}
+}
+```
+
+## Reproducibility
+
+```bash
+git clone https://huggingface.co/Entrit/tritllm-codec
+cd tritllm-codec
+python quantize_model_v2.py --model Qwen/Qwen2.5-3B --configs uniform-d3 --out ./out
+```