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---
language:
- en
- zh
- id
- th
- vi
- ms
- lo
datasets:
- cerebras/SlimPajama-627B
- Skywork/SkyPile-150B
- allenai/MADLAD-400
- cc100
tags:
- multilingual
- sea
- sailor
- llama-cpp
- gguf-my-repo
license: apache-2.0
base_model: sail/Sailor-7B
model-index:
- name: Sailor-7B
results:
- task:
type: text-generation
dataset:
name: XQuAD-Thai
type: XQuAD-Thai
metrics:
- type: EM (3-Shot)
value: 57.88
name: EM (3-Shot)
- type: F1 (3-Shot)
value: 71.06
name: F1 (3-Shot)
- task:
type: text-generation
dataset:
name: TyDiQA-Indonesian
type: TyDiQA-Indonesian
metrics:
- type: EM (3-Shot)
value: 60.53
name: EM (3-Shot)
- type: F1 (3-Shot)
value: 75.42
name: F1 (3-Shot)
- task:
type: text-generation
dataset:
name: XQuAD-Vietnamese
type: XQuAD-Vietnamese
metrics:
- type: EM (3-Shot)
value: 53.81
name: EM (3-Shot)
- type: F1 (3-Shot)
value: 74.62
name: F1 (3-Shot)
- task:
type: text-generation
dataset:
name: XCOPA-Thai
type: XCOPA-Thai
metrics:
- type: EM (3-Shot)
value: 59.0
name: EM (3-Shot)
- task:
type: text-generation
dataset:
name: XCOPA-Indonesian
type: XCOPA-Indonesian
metrics:
- type: EM (3-Shot)
value: 72.2
name: EM (3-Shot)
- task:
type: text-generation
dataset:
name: XCOPA-Vietnamese
type: XCOPA-Vietnamese
metrics:
- type: EM (3-Shot)
value: 72.2
name: EM (3-Shot)
- task:
type: text-generation
dataset:
name: M3Exam-Thai
type: M3Exam-Thai
metrics:
- type: EM (3-Shot)
value: 30.0
name: EM (3-Shot)
- task:
type: text-generation
dataset:
name: M3Exam-Indonesian
type: M3Exam-Indonesian
metrics:
- type: EM (3-Shot)
value: 32.88
name: EM (3-Shot)
- task:
type: text-generation
dataset:
name: M3Exam-Vietnamese
type: M3Exam-Vietnamese
metrics:
- type: EM (3-Shot)
value: 44.1
name: EM (3-Shot)
- task:
type: text-generation
dataset:
name: BELEBELE-Thai
type: BELEBELE-Thai
metrics:
- type: EM (3-Shot)
value: 41.56
name: EM (3-Shot)
- task:
type: text-generation
dataset:
name: BELEBELE-Indonesian
type: BELEBELE-Indonesian
metrics:
- type: EM (3-Shot)
value: 44.33
name: EM (3-Shot)
- task:
type: text-generation
dataset:
name: BELEBELE-Vietnamese
type: BELEBELE-Vietnamese
metrics:
- type: EM (3-Shot)
value: 45.33
name: EM (3-Shot)
---
# AIronMind/Sailor-7B-Q4_K_M-GGUF
This model was converted to GGUF format from [`sail/Sailor-7B`](https://huggingface.co/sail/Sailor-7B) 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/sail/Sailor-7B) 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 AIronMind/Sailor-7B-Q4_K_M-GGUF --hf-file sailor-7b-q4_k_m.gguf -p "The meaning to life and the universe is"
```
### Server:
```bash
llama-server --hf-repo AIronMind/Sailor-7B-Q4_K_M-GGUF --hf-file sailor-7b-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 AIronMind/Sailor-7B-Q4_K_M-GGUF --hf-file sailor-7b-q4_k_m.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo AIronMind/Sailor-7B-Q4_K_M-GGUF --hf-file sailor-7b-q4_k_m.gguf -c 2048
```
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