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---
library_name: transformers
license: apache-2.0
language:
- en
- zh
- es
- de
- ar
- ru
- ja
- ko
- hi
- sk
- vi
- tr
- fi
- id
- fa
- 'no'
- th
- sv
- pt
- da
- bn
- te
- ro
- it
- fr
- nl
- sw
- pl
- hu
- cs
- el
- uk
- mr
- ta
- tl
- bg
- lt
- ur
- he
- gu
- kn
- am
- kk
- hr
- uz
- jv
- ca
- az
- ms
- sr
- sl
- yo
- lv
- is
- ha
- ka
- et
- bs
- hy
- ml
- pa
- mt
- km
- sq
- or
- as
- my
- mn
- af
- be
- ga
- mk
- cy
- gl
- ceb
- la
- yi
- lb
- tg
- gd
- ne
- ps
- eu
- ky
- ku
- si
- ht
- eo
- lo
- fy
- sd
- mg
- so
- ckb
- su
- nn
datasets:
- lightblue/reranker_continuous_filt_max7_train
base_model: lightblue/lb-reranker-0.5B-v1.0
pipeline_tag: text-generation
tags:
- reranker
- llama-cpp
- gguf-my-repo
widget:
- text: '<<<Query>>>
How many languages has LB-Reranker been trained on?
<<<Context>>>
LB-Reranker has been trained on more than 95 languages.'
example_title: Positive example (7/7)
- text: '<<<Query>>>
How many languages has LB-Reranker been trained on?
<<<Context>>>
AA-Reranker is applicable to a broad range of use cases.'
example_title: Negative example (2/7)
---
# jimi0209/lb-reranker-0.5B-v1.0-Q5_K_M-GGUF
This model was converted to GGUF format from [`lightblue/lb-reranker-0.5B-v1.0`](https://huggingface.co/lightblue/lb-reranker-0.5B-v1.0) 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/lightblue/lb-reranker-0.5B-v1.0) 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 jimi0209/lb-reranker-0.5B-v1.0-Q5_K_M-GGUF --hf-file lb-reranker-0.5b-v1.0-q5_k_m.gguf -p "The meaning to life and the universe is"
```
### Server:
```bash
llama-server --hf-repo jimi0209/lb-reranker-0.5B-v1.0-Q5_K_M-GGUF --hf-file lb-reranker-0.5b-v1.0-q5_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 jimi0209/lb-reranker-0.5B-v1.0-Q5_K_M-GGUF --hf-file lb-reranker-0.5b-v1.0-q5_k_m.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo jimi0209/lb-reranker-0.5B-v1.0-Q5_K_M-GGUF --hf-file lb-reranker-0.5b-v1.0-q5_k_m.gguf -c 2048
```
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