---
title: bce-embedding-base_v1-Q4_K_M-GGUF
canonical_url: "https://www.modelscope.cn/models/LLM-Research/bce-embedding-base_v1-Q4_K_M-GGUF"
md_url: "https://www.modelscope.cn/models/LLM-Research/bce-embedding-base_v1-Q4_K_M-GGUF.md"
repository: LLM-Research/bce-embedding-base_v1-Q4_K_M-GGUF
last_updated: 2024-09-10
license: apache-2.0
pipeline_tag: feature-extraction
tasks:
  - feature-extraction
library_name:
  - sentence-transformers
  - gguf
  - pytorch
frameworks:
  - pytorch
language:
  - en
  - zh
downloads: 2257
stars: 0
tags:
  - sentence-transformers
  - feature-extraction
  - sentence-similarity
  - transformers
  - llama-cpp
  - gguf-my-repo
  - gguf
---

# bce-embedding-base_v1-Q4_K_M-GGUF

> bce-embedding-base_v1-Q4_K_M-GGUF - LLM-Research 在 ModelScope 开源的模型。opengf/bce-embedding-basev1-Q4KM-GGUF This model was converted to GGUF format from maidalun1020/bce-embedding-basev1 using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the…

LLM-Research/bce-embedding-base_v1-Q4_K_M-GGUF 是 ModelScope 魔搭社区上的feature-extraction模型，采用 apache-2.0 许可。

- **Repository**: LLM-Research/bce-embedding-base_v1-Q4_K_M-GGUF
- **License**: apache-2.0
- **Tasks**: feature-extraction
- **Tags**: sentence-transformers, feature-extraction, sentence-similarity, transformers, llama-cpp, gguf-my-repo, gguf
- **Downloads**: 2257
- **Stars**: 0
- **Last updated**: 2024-09-10

Source: https://www.modelscope.cn/models/LLM-Research/bce-embedding-base_v1-Q4_K_M-GGUF

---

# opengf/bce-embedding-base_v1-Q4_K_M-GGUF
This model was converted to GGUF format from [`maidalun1020/bce-embedding-base_v1`](https://huggingface.co/maidalun1020/bce-embedding-base_v1) 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/maidalun1020/bce-embedding-base_v1) 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 opengf/bce-embedding-base_v1-Q4_K_M-GGUF --hf-file bce-embedding-base_v1-q4_k_m.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo opengf/bce-embedding-base_v1-Q4_K_M-GGUF --hf-file bce-embedding-base_v1-q4_k_m.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 opengf/bce-embedding-base_v1-Q4_K_M-GGUF --hf-file bce-embedding-base_v1-q4_k_m.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo opengf/bce-embedding-base_v1-Q4_K_M-GGUF --hf-file bce-embedding-base_v1-q4_k_m.gguf -c 2048
```