---
license: mit
base_model: HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
language:
- zh
- en
---

Using [llama.cpp](https://github.com/ggml-org/llama.cpp) for GGUF conversion.

Original model: [HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1](https://huggingface.co/HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1)

Run them directly with [llama.cpp](https://github.com/ggerganov/llama.cpp):

```Bash
./llama-embedding \
  --batch-size 512 \
  --ctx-size 512 \
  -m KaLM-embedding-multilingual-mini-instruct-v1-GGUF/model.f32.gguf \
  --pooling mean \
  -p "this is a test sentence for llama cpp"
```

It is important to note that this model uses the mean pooling method, so the `--pooling` parameter needs to be specified as `mean` when invoking it. 

Our tests on [LM Studio](https://lmstudio.ai/) have not yet been successful, and it is unclear whether this is related to the default pooling method used by LM Studio. 

If any developers are familiar with how to specify the pooling method for embedding models in LM Studio, we welcome you to contact us for further discussion via the email: yanshek.woo@gmail.com