commit 23a1c646288c287cf6cabf5f987a5c0a716be319 Author: ModelHub XC Date: Fri Sep 4 19:50:16 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: liodon-ai/Qwen2.5-Coder-7B-Instruct-imatrix-GGUF Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..daf6388 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,42 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs 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@@ +--- +license: other +base_model: Qwen/Qwen2.5-Coder-7B-Instruct +base_model_relation: quantized +pipeline_tag: text-generation +library_name: gguf +tags: +- gguf +- ollama +- local-llm +- llama.cpp +- lm-studio +- quantized +- imatrix +- sub-4-bit +- qwen2 +- codeqwen +quantized_by: liodon-ai +--- + +# Qwen2.5-Coder-7B-Instruct — iMatrix GGUF + +GGUF quantizations of [Qwen/Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct), published by [Liodon AI](https://huggingface.co/liodon-ai). + +## Quick Start + +**llama.cpp** +```bash +llama-cli -hf liodon-ai/Qwen2.5-Coder-7B-Instruct-imatrix-GGUF:Q4_K_M +``` + +**Ollama** +```bash +ollama run hf.co/liodon-ai/Qwen2.5-Coder-7B-Instruct-imatrix-GGUF:Q4_K_M +``` + +**LM Studio / Jan** — search `liodon-ai/Qwen2.5-Coder-7B-Instruct-imatrix-GGUF` and pick your quant. + +## Quants + +| Quant | Size | VRAM est. | Notes | +|-------|------|-----------|-------| +| `IQ2_M` | 2.78 GB | ~3 GB | 2-bit, iMatrix — smallest usable | +| `IQ3_M` | 3.57 GB | ~4 GB | 3-bit, iMatrix — great quality/size tradeoff | +| `IQ4_XS` | 4.22 GB | ~5 GB | 4-bit extra-small, iMatrix | +| `Q4_K_M` | 4.68 GB | ~5 GB | 4-bit, iMatrix-calibrated (recommended) | +| `Q5_K_M` | 5.44 GB | ~6 GB | 5-bit, iMatrix-calibrated | +| `Q6_K` | 6.25 GB | ~7 GB | 6-bit, iMatrix-calibrated, near-lossless | +| `Q8_0` | 8.10 GB | ~9 GB | 8-bit, essentially lossless | + + +## What is iMatrix? + +Standard quantization treats all weights equally. iMatrix runs 128 calibration chunks through +the full-precision model to find which weights matter most, then allocates more precision where +it counts. At Q2/Q3/Q4 this means noticeably better coherence and instruction-following — +**same file size, better output**. + +Calibration: 2M tokens of [WikiText-103](https://huggingface.co/datasets/wikitext). + +> Also see plain (non-iMatrix) quants: `liodon-ai/Qwen2.5-Coder-7B-Instruct-GGUF` + +## Source + +- **Model**: [Qwen/Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct) +- **License**: other + +--- +*Quantized by [Liodon AI](https://huggingface.co/liodon-ai)*