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---
language:
- zh
base_model: OpenSearch-AI/Ops-MoA-Yuan-embedding-1.0
pipeline_tag: feature-extraction
tags:
- mteb
- sentence-transformers
- llama-cpp
- gguf-my-repo
model-index:
- name: Ops-MoA-Yuan-embedding-1.0
results:
- task:
type: Retrieval
dataset:
name: MTEB CmedqaRetrieval
type: C-MTEB/CmedqaRetrieval
config: default
split: dev
revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
metrics:
- type: ndcg_at_10
value: 51.461
- task:
type: Retrieval
dataset:
name: MTEB CovidRetrieval
type: C-MTEB/CovidRetrieval
config: default
split: dev
revision: 1271c7809071a13532e05f25fb53511ffce77117
metrics:
- type: ndcg_at_10
value: 93.2
- task:
type: Retrieval
dataset:
name: MTEB DuRetrieval
type: C-MTEB/DuRetrieval
config: default
split: dev
revision: a1a333e290fe30b10f3f56498e3a0d911a693ced
metrics:
- type: ndcg_at_10
value: 89.84
- task:
type: Retrieval
dataset:
name: MTEB EcomRetrieval
type: C-MTEB/EcomRetrieval
config: default
split: dev
revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
metrics:
- type: ndcg_at_10
value: 71.084
- task:
type: Retrieval
dataset:
name: MTEB MMarcoRetrieval
type: C-MTEB/MMarcoRetrieval
config: default
split: dev
revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
metrics:
- type: ndcg_at_10
value: 82.43
- task:
type: Retrieval
dataset:
name: MTEB MedicalRetrieval
type: C-MTEB/MedicalRetrieval
config: default
split: dev
revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
metrics:
- type: ndcg_at_10
value: 74.848
- task:
type: Retrieval
dataset:
name: MTEB T2Retrieval
type: C-MTEB/T2Retrieval
config: default
split: dev
revision: 8731a845f1bf500a4f111cf1070785c793d10e64
metrics:
- type: ndcg_at_10
value: 85.784
- task:
type: Retrieval
dataset:
name: MTEB VideoRetrieval
type: C-MTEB/VideoRetrieval
config: default
split: dev
revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
metrics:
- type: ndcg_at_10
value: 79.513
---
# 6san/Ops-MoA-Yuan-embedding-1.0-Q8_0-GGUF
This model was converted to GGUF format from [`OpenSearch-AI/Ops-MoA-Yuan-embedding-1.0`](https://huggingface.co/OpenSearch-AI/Ops-MoA-Yuan-embedding-1.0) 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/OpenSearch-AI/Ops-MoA-Yuan-embedding-1.0) 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 6san/Ops-MoA-Yuan-embedding-1.0-Q8_0-GGUF --hf-file ops-moa-yuan-embedding-1.0-q8_0.gguf -p "The meaning to life and the universe is"
```
### Server:
```bash
llama-server --hf-repo 6san/Ops-MoA-Yuan-embedding-1.0-Q8_0-GGUF --hf-file ops-moa-yuan-embedding-1.0-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 6san/Ops-MoA-Yuan-embedding-1.0-Q8_0-GGUF --hf-file ops-moa-yuan-embedding-1.0-q8_0.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo 6san/Ops-MoA-Yuan-embedding-1.0-Q8_0-GGUF --hf-file ops-moa-yuan-embedding-1.0-q8_0.gguf -c 2048
```
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