README.md

---
library_name: sentence-transformers
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- llama-cpp
- gguf-my-repo
base_model: avemio/GRAG-BGE-M3-MERGED-x-SNOWFLAKE-ARCTIC-HESSIAN-AI
base_model_relation: merge
widget:
- source_sentence: 'search_query: i love autotrain'
  sentences:
  - 'search_query: huggingface auto train'
  - 'search_query: hugging face auto train'
  - 'search_query: i love autotrain'
pipeline_tag: sentence-similarity
datasets:
- avemio/GRAG-EMBEDDING-TRIPLES-HESSIAN-AI
license: mit
language:
- de
- en
---

# avemio-digital/GRAG-BGE-M3-MERGED-x-SNOWFLAKE-ARCTIC-HESSIAN-AI-Q8_0-GGUF
This model was converted to GGUF format from [`avemio/GRAG-BGE-M3-MERGED-x-SNOWFLAKE-ARCTIC-HESSIAN-AI`](https://huggingface.co./avemio/GRAG-BGE-M3-MERGED-x-SNOWFLAKE-ARCTIC-HESSIAN-AI) 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./avemio/GRAG-BGE-M3-MERGED-x-SNOWFLAKE-ARCTIC-HESSIAN-AI) 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 avemio-digital/GRAG-BGE-M3-MERGED-x-SNOWFLAKE-ARCTIC-HESSIAN-AI-Q8_0-GGUF --hf-file grag-bge-m3-merged-x-snowflake-arctic-hessian-ai-q8_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo avemio-digital/GRAG-BGE-M3-MERGED-x-SNOWFLAKE-ARCTIC-HESSIAN-AI-Q8_0-GGUF --hf-file grag-bge-m3-merged-x-snowflake-arctic-hessian-ai-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 avemio-digital/GRAG-BGE-M3-MERGED-x-SNOWFLAKE-ARCTIC-HESSIAN-AI-Q8_0-GGUF --hf-file grag-bge-m3-merged-x-snowflake-arctic-hessian-ai-q8_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo avemio-digital/GRAG-BGE-M3-MERGED-x-SNOWFLAKE-ARCTIC-HESSIAN-AI-Q8_0-GGUF --hf-file grag-bge-m3-merged-x-snowflake-arctic-hessian-ai-q8_0.gguf -c 2048
```