初始化项目，由ModelHub XC社区提供模型

Model: mradermacher/YuLan-Mini-GGUF
Source: Original Platform

README.md

@@ -0,0 +1,101 @@
+---
+arxiv: 2412.17743
+base_model: yulan-team/YuLan-Mini
+datasets:
+- yulan-team/YuLan-Mini-Datasets
+- HuggingFaceFW/fineweb-edu
+- bigcode/the-stack-v2
+- mlfoundations/dclm-baseline-1.0
+- math-ai/AutoMathText
+- gair-prox/open-web-math-pro
+- RUC-AIBOX/long_form_thought_data_5k
+- internlm/Lean-Workbook
+- internlm/Lean-Github
+- deepseek-ai/DeepSeek-Prover-V1
+- ScalableMath/Lean-STaR-base
+- ScalableMath/Lean-STaR-plus
+- ScalableMath/Lean-CoT-base
+- ScalableMath/Lean-CoT-plus
+- opencsg/chinese-fineweb-edu
+- liwu/MNBVC
+- vikp/textbook_quality_programming
+- HuggingFaceTB/smollm-corpus
+- OpenCoder-LLM/opc-annealing-corpus
+- OpenCoder-LLM/opc-sft-stage1
+- OpenCoder-LLM/opc-sft-stage2
+- XinyaoHu/AMPS_mathematica
+- deepmind/math_dataset
+- mrfakename/basic-math-10m
+- microsoft/orca-math-word-problems-200k
+- AI-MO/NuminaMath-CoT
+- HuggingFaceTB/cosmopedia
+- MU-NLPC/Calc-ape210k
+- manu/project_gutenberg
+- storytracer/LoC-PD-Books
+- allenai/dolma
+language:
+- en
+- zh
+library_name: transformers
+license: mit
+quantized_by: mradermacher
+tags:
+- code
+- math
+---
+## About
+
+<!-- ### quantize_version: 2 -->
+<!-- ### output_tensor_quantised: 1 -->
+<!-- ### convert_type: hf -->
+<!-- ### vocab_type:  -->
+<!-- ### tags:  -->
+static quants of https://huggingface.co/yulan-team/YuLan-Mini
+
+<!-- provided-files -->
+weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
+## Usage
+
+If you are unsure how to use GGUF files, refer to one of [TheBloke's
+READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
+more details, including on how to concatenate multi-part files.
+
+## Provided Quants
+
+(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
+
+| Link | Type | Size/GB | Notes |
+|:-----|:-----|--------:|:------|
+| [GGUF](https://huggingface.co/mradermacher/YuLan-Mini-GGUF/resolve/main/YuLan-Mini.Q3_K_S.gguf) | Q3_K_S | 1.6 |  |
+| [GGUF](https://huggingface.co/mradermacher/YuLan-Mini-GGUF/resolve/main/YuLan-Mini.Q2_K.gguf) | Q2_K | 1.6 |  |
+| [GGUF](https://huggingface.co/mradermacher/YuLan-Mini-GGUF/resolve/main/YuLan-Mini.IQ4_XS.gguf) | IQ4_XS | 1.6 |  |
+| [GGUF](https://huggingface.co/mradermacher/YuLan-Mini-GGUF/resolve/main/YuLan-Mini.Q3_K_M.gguf) | Q3_K_M | 1.7 | lower quality |
+| [GGUF](https://huggingface.co/mradermacher/YuLan-Mini-GGUF/resolve/main/YuLan-Mini.Q3_K_L.gguf) | Q3_K_L | 1.7 |  |
+| [GGUF](https://huggingface.co/mradermacher/YuLan-Mini-GGUF/resolve/main/YuLan-Mini.Q4_K_S.gguf) | Q4_K_S | 1.8 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/YuLan-Mini-GGUF/resolve/main/YuLan-Mini.Q4_K_M.gguf) | Q4_K_M | 1.9 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/YuLan-Mini-GGUF/resolve/main/YuLan-Mini.Q5_K_S.gguf) | Q5_K_S | 2.0 |  |
+| [GGUF](https://huggingface.co/mradermacher/YuLan-Mini-GGUF/resolve/main/YuLan-Mini.Q5_K_M.gguf) | Q5_K_M | 2.1 |  |
+| [GGUF](https://huggingface.co/mradermacher/YuLan-Mini-GGUF/resolve/main/YuLan-Mini.Q6_K.gguf) | Q6_K | 2.7 | very good quality |
+| [GGUF](https://huggingface.co/mradermacher/YuLan-Mini-GGUF/resolve/main/YuLan-Mini.Q8_0.gguf) | Q8_0 | 2.7 | fast, best quality |
+| [GGUF](https://huggingface.co/mradermacher/YuLan-Mini-GGUF/resolve/main/YuLan-Mini.f16.gguf) | f16 | 5.0 | 16 bpw, overkill |
+
+Here is a handy graph by ikawrakow comparing some lower-quality quant
+types (lower is better):
+
+![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
+
+And here are Artefact2's thoughts on the matter:
+https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
+
+## FAQ / Model Request
+
+See https://huggingface.co/mradermacher/model_requests for some answers to
+questions you might have and/or if you want some other model quantized.
+
+## Thanks
+
+I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
+me use its servers and providing upgrades to my workstation to enable
+this work in my free time.
+
+<!-- end -->