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Model: Entrit/Mistral-7B-v0.3-trit-uniform-d4
Source: Original Platform

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.mirrored

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+2026-04-16T00:25:13.410997

README.md

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+---
+license: apache-2.0
+base_model: mistralai/Mistral-7B-v0.3
+tags:
+  - quantization
+  - ternary
+  - balanced-ternary
+  - tritllm
+library_name: transformers
+---
+
+# Mistral-7B-v0.3-trit-uniform-d4
+
+Balanced ternary quantization of [`mistralai/Mistral-7B-v0.3`](https://huggingface.co/mistralai/Mistral-7B-v0.3) at depth **d=4** (81 levels per weight, **6.64 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/Mistral-7B-v0.3-trit-uniform-d4")
+tokenizer = AutoTokenizer.from_pretrained("Entrit/Mistral-7B-v0.3-trit-uniform-d4")
+```
+
+The weights are dequantized to FP16 for stock-`transformers` compatibility. The on-disk size is therefore the same as the FP16 source. The 6.64-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 | [`mistralai/Mistral-7B-v0.3`](https://huggingface.co/mistralai/Mistral-7B-v0.3) |
+| Depth | d=4 (81 levels) |
+| Bits per weight | 6.64 |
+| 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 mistralai/Mistral-7B-v0.3 --configs uniform-d4 --out ./out
+```

config.json

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+{
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "dtype": "float16",
+  "eos_token_id": 2,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pad_token_id": null,
+  "rms_norm_eps": 1e-05,
+  "rope_parameters": {
+    "rope_theta": 1000000.0,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "transformers_version": "5.5.3",
+  "use_cache": true,
+  "vocab_size": 32768
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "5.5.3"
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:777971af468a5e908e76c36f0df364e5599582ec6373194f083b98b6e29d42c9
+size 14496080848

tokenizer_config.json

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+{
+  "add_prefix_space": true,
+  "backend": "tokenizers",
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "is_local": true,
+  "legacy": false,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "</s>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "TokenizersBackend",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}