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---
license: Apache License 2.0
#model-type:
##如 gpt、phi、llama、chatglm、baichuan 等
#- gpt
#domain:
##如 nlp、cv、audio、multi-modal
#- nlp
#language:
##语言代码列表 https://help.aliyun.com/document_detail/215387.html?spm=a2c4g.11186623.0.0.9f8d7467kni6Aa
#- cn
#metrics:
##如 CIDEr、Blue、ROUGE 等
#- CIDEr
#tags:
##各种自定义,包括 pretrained、fine-tuned、instruction-tuned、RL-tuned 等训练方法和其他
#- pretrained
#tools:
##如 vllm、fastchat、llamacpp、AdaSeq 等
#- vllm
base_model: prithivMLmods/Horologium-QwenC-1.5B
language:
- en
library_name: transformers
license: apache-2.0
pipeline_tag: text-generation
tags:
- text-generation-inference
- code
- math
- RL
- QwenC
- llama-cpp
- gguf-my-repo
---
### 当前模型的贡献者未提供更加详细的模型介绍。模型文件和权重,可浏览“模型文件”页面获取。
#### 您可以通过如下git clone命令或者ModelScope SDK来下载模型
SDK下载
# prithivMLmods/Horologium-QwenC-1.5B-Q8_0-GGUF
This model was converted to GGUF format from [`prithivMLmods/Horologium-QwenC-1.5B`](https://huggingface.co/prithivMLmods/Horologium-QwenC-1.5B) 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/prithivMLmods/Horologium-QwenC-1.5B) for more details on the model.
## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
```bash
#安装ModelScope
pip install modelscope
brew install llama.cpp
```
```python
#SDK模型下载
from modelscope import snapshot_download
model_dir = snapshot_download('prithivMLmods/Horologium-QwenC-1.5B-Q8_0-GGUF')
```
Git下载
```
#Git模型下载
git clone https://www.modelscope.cn/prithivMLmods/Horologium-QwenC-1.5B-Q8_0-GGUF.git
Invoke the llama.cpp server or the CLI.
### CLI:
```bash
llama-cli --hf-repo prithivMLmods/Horologium-QwenC-1.5B-Q8_0-GGUF --hf-file horologium-qwenc-1.5b-q8_0.gguf -p "The meaning to life and the universe is"
```
<p style="color: lightgrey;">如果您是本模型的贡献者,我们邀请您根据<a href="https://modelscope.cn/docs/ModelScope%E6%A8%A1%E5%9E%8B%E6%8E%A5%E5%85%A5%E6%B5%81%E7%A8%8B%E6%A6%82%E8%A7%88" style="color: lightgrey; text-decoration: underline;">模型贡献文档</a>,及时完善模型卡片内容。</p>
### Server:
```bash
llama-server --hf-repo prithivMLmods/Horologium-QwenC-1.5B-Q8_0-GGUF --hf-file horologium-qwenc-1.5b-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 prithivMLmods/Horologium-QwenC-1.5B-Q8_0-GGUF --hf-file horologium-qwenc-1.5b-q8_0.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo prithivMLmods/Horologium-QwenC-1.5B-Q8_0-GGUF --hf-file horologium-qwenc-1.5b-q8_0.gguf -c 2048
```

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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}

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