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---
license: mit
library_name: transformers
pipeline_tag: text-generation
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
tags:
- code
- math
- llama-cpp
- gguf-my-repo
arxiv: 2412.17743
base_model: yulan-team/YuLan-Mini
model-index:
- name: YuLan-Mini
results:
- task:
type: text-generation
dataset:
name: HumanEval
type: openai_humaneval
metrics:
- type: pass@1
value: 0.64
name: pass@1
verified: false
- task:
type: text-generation
dataset:
name: MBPP
type: mbpp
metrics:
- type: pass@1
value: 0.659
name: pass@1
verified: false
- task:
type: text-generation
dataset:
name: MATH-500
type: math-500
metrics:
- type: maj@1
value: 0.378
name: maj@1
verified: false
- task:
type: text-generation
dataset:
name: GSM8K
type: gsm8k
metrics:
- type: maj@1
value: 0.684
name: maj@1
verified: false
---
# matrixportal/YuLan-Mini-Q8_0-GGUF
This model was converted to GGUF format from [`yulan-team/YuLan-Mini`](https://huggingface.co/yulan-team/YuLan-Mini) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/yulan-team/YuLan-Mini) for more details on the model.
## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
```bash
brew install llama.cpp
```
Invoke the llama.cpp server or the CLI.
### CLI:
```bash
llama-cli --hf-repo matrixportal/YuLan-Mini-Q8_0-GGUF --hf-file yulan-mini-q8_0.gguf -p "The meaning to life and the universe is"
```
### Server:
```bash
llama-server --hf-repo matrixportal/YuLan-Mini-Q8_0-GGUF --hf-file yulan-mini-q8_0.gguf -c 2048
```
Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```
Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```
Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo matrixportal/YuLan-Mini-Q8_0-GGUF --hf-file yulan-mini-q8_0.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo matrixportal/YuLan-Mini-Q8_0-GGUF --hf-file yulan-mini-q8_0.gguf -c 2048
```
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