初始化项目，由ModelHub XC社区提供模型

Model: yasserrmd/glm5.1-distill-GGUF
Source: Original Platform

README.md

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+---
+license: apache-2.0
+language:
+- en
+library_name: gguf
+pipeline_tag: text-generation
+base_model: yasserrmd/glm5.1-distill
+tags:
+- gguf
+- llama.cpp
+- lfm2
+- liquid-ai
+- edge
+- text-generation-inference
+- conversational
+---
+
+# glm5.1-distill-GGUF
+
+GGUF quantizations of [`yasserrmd/glm5.1-distill`](https://huggingface.co/yasserrmd/glm5.1-distill),
+produced with `convert_hf_to_gguf.py` and `llama-quantize` from
+[`ggml-org/llama.cpp`](https://github.com/ggml-org/llama.cpp).
+
+The quant ladder mirrors Liquid AI's own LFM2.5-1.2B GGUF releases
+(e.g. [`LiquidAI/LFM2.5-1.2B-Base-GGUF`](https://huggingface.co/LiquidAI/LFM2.5-1.2B-Base-GGUF)).
+
+## Files
+
+| File | Quantization | Size |
+|------|--------------|------|
+| `glm5.1-distill-BF16.gguf` | BF16 | 2.18 GB |
+| `glm5.1-distill-Q4_0.gguf` | Q4_0 | 664 MB |
+| `glm5.1-distill-Q4_K_M.gguf` | Q4_K_M | 697 MB |
+| `glm5.1-distill-Q5_K_M.gguf` | Q5_K_M | 804 MB |
+| `glm5.1-distill-Q6_K.gguf` | Q6_K | 918 MB |
+| `glm5.1-distill-Q8_0.gguf` | Q8_0 | 1.16 GB |
+
+## Quickstart with `llama.cpp`
+
+Run any quant directly from the Hub:
+
+```bash
+llama-cli -hf yasserrmd/glm5.1-distill-GGUF:Q4_K_M     --jinja --ctx-size 32768     --temp 0.1 --top-k 50 --top-p 0.1 --repeat-penalty 1.05
+```
+
+Or download manually and serve via `llama-server`:
+
+```bash
+huggingface-cli download yasserrmd/glm5.1-distill-GGUF     --include "*Q4_K_M*" --local-dir ./glm5.1-distill-GGUF
+
+llama-server     --model ./glm5.1-distill-GGUF/glm5.1-distill-Q4_K_M.gguf     --alias "yasserrmd/glm5.1-distill"     --threads -1 --n-gpu-layers 99     --ctx-size 32768 --port 8001     --temp 0.1 --top-k 50 --top-p 0.1 --repeat-penalty 1.05     --jinja
+```
+
+The recommended sampling parameters above are the official ones published by
+Liquid AI for the LFM2.5 family.
+
+## Quickstart with Ollama
+
+```bash
+ollama run hf.co/yasserrmd/glm5.1-distill-GGUF:Q4_K_M
+```
+
+## Choosing a quant
+
+| Use case | Recommended |
+|----------|-------------|
+| Maximum quality, plenty of RAM | `Q8_0` or `Q6_K` |
+| Balanced default | `Q4_K_M` (matches Liquid AI's recommendation) |
+| Smallest footprint, mobile / IoT | `Q4_0` |
+| Lossless reference | `BF16` (only if you need it for further re-quantization) |
+
+> **Note**: imatrix-based quantization is currently not supported for the LFM2
+> architecture in upstream llama.cpp ([issue #14979](https://github.com/ggml-org/llama.cpp/issues/14979)).
+> These files are plain k-quants, the same scheme used in Liquid AI's official
+> GGUF releases.
+
+## Source model
+
+For training data, hyperparameters, evaluation, and limitations see the source
+repo: [`yasserrmd/glm5.1-distill`](https://huggingface.co/yasserrmd/glm5.1-distill).