Instructions to use OrionStarAI/Orion-14B-Base-Int4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OrionStarAI/Orion-14B-Base-Int4 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="OrionStarAI/Orion-14B-Base-Int4", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("OrionStarAI/Orion-14B-Base-Int4", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use OrionStarAI/Orion-14B-Base-Int4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "OrionStarAI/Orion-14B-Base-Int4"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OrionStarAI/Orion-14B-Base-Int4",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/OrionStarAI/Orion-14B-Base-Int4

SGLang

How to use OrionStarAI/Orion-14B-Base-Int4 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "OrionStarAI/Orion-14B-Base-Int4" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OrionStarAI/Orion-14B-Base-Int4",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "OrionStarAI/Orion-14B-Base-Int4" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OrionStarAI/Orion-14B-Base-Int4",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use OrionStarAI/Orion-14B-Base-Int4 with Docker Model Runner:
```
docker model run hf.co/OrionStarAI/Orion-14B-Base-Int4
```

renillhuang commited on Mar 26, 2024

Commit

cf72e32

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1 Parent(s): 84b588f

Update README_ko.md

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Add Discord link for Korean edition

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@@ -367,7 +367,8 @@ Orion-14B：안녕하세요, 제 명칭은 ChatMax입니다. OrionStar에서 개
 ***대형 모델 응용 구현 필요가 있으신 회사께서 저희와 연락하는 것을 환영한다***<br>
 **문의 전화:** 400-898-7779<br>
-**이메일:** ai@orionstar.com
 <div align="center">
   <img src="./assets/imgs/wechat_group.jpg" alt="wechat" width="40%" />

 ***대형 모델 응용 구현 필요가 있으신 회사께서 저희와 연락하는 것을 환영한다***<br>
 **문의 전화:** 400-898-7779<br>
+**이메일:** ai@orionstar.com<br>
+**Discord 커뮤니티 링크:** https://discord.gg/zumjDWgdAs
 <div align="center">
   <img src="./assets/imgs/wechat_group.jpg" alt="wechat" width="40%" />