Instructions to use Linly-AI/Chinese-LLaMA-2-13B-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Linly-AI/Chinese-LLaMA-2-13B-hf with Transformers:

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

pipe = pipeline("text-generation", model="Linly-AI/Chinese-LLaMA-2-13B-hf")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Linly-AI/Chinese-LLaMA-2-13B-hf")
model = AutoModelForCausalLM.from_pretrained("Linly-AI/Chinese-LLaMA-2-13B-hf")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Linly-AI/Chinese-LLaMA-2-13B-hf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Linly-AI/Chinese-LLaMA-2-13B-hf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Linly-AI/Chinese-LLaMA-2-13B-hf",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Linly-AI/Chinese-LLaMA-2-13B-hf

SGLang

How to use Linly-AI/Chinese-LLaMA-2-13B-hf 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 "Linly-AI/Chinese-LLaMA-2-13B-hf" \
    --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": "Linly-AI/Chinese-LLaMA-2-13B-hf",
		"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 "Linly-AI/Chinese-LLaMA-2-13B-hf" \
        --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": "Linly-AI/Chinese-LLaMA-2-13B-hf",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Linly-AI/Chinese-LLaMA-2-13B-hf with Docker Model Runner:
```
docker model run hf.co/Linly-AI/Chinese-LLaMA-2-13B-hf
```

更新readme

by sirilong - opened Aug 9, 2023

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+17

-2

Files changed (1) hide show

README.md +17 -2

README.md CHANGED Viewed

@@ -1,6 +1,21 @@
-基于中英文混合语料增量训练，词表扩充汉字。
-训练细节和benchmark指标： https://github.com/CVI-SZU/Linly
 ```python

+---
+language:
+- zh
+- en
+tags:
+- LLaMA2
+- Linly
+- Chinese-LLaMA2
+---
+# Chinese-LLaMA-2-13B
+Linly-Chinese-LLaMA2 基于 LLaMA2进行中文化训练，使用课程学习方法跨语言迁移，词表针对中文重新设计，数据分布更均衡，收敛更稳定。
+<p align="left">
+  训练细节和benchmark指标详见 💻 <a href="https://github.com/CVI-SZU/Linly" target="_blank">Github Repo</a>
+</p>
 ```python