Instructions to use LinkSoul/Chinese-Llama-2-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LinkSoul/Chinese-Llama-2-7b with Transformers:

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

pipe = pipeline("text-generation", model="LinkSoul/Chinese-Llama-2-7b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("LinkSoul/Chinese-Llama-2-7b")
model = AutoModelForCausalLM.from_pretrained("LinkSoul/Chinese-Llama-2-7b")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use LinkSoul/Chinese-Llama-2-7b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LinkSoul/Chinese-Llama-2-7b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LinkSoul/Chinese-Llama-2-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/LinkSoul/Chinese-Llama-2-7b

SGLang

How to use LinkSoul/Chinese-Llama-2-7b 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 "LinkSoul/Chinese-Llama-2-7b" \
    --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": "LinkSoul/Chinese-Llama-2-7b",
		"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 "LinkSoul/Chinese-Llama-2-7b" \
        --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": "LinkSoul/Chinese-Llama-2-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use LinkSoul/Chinese-Llama-2-7b with Docker Model Runner:
```
docker model run hf.co/LinkSoul/Chinese-Llama-2-7b
```

oobabooga-windows 出错 ! 选的是llmam.cpp

#11

by aldennX - opened Aug 6, 2023

Discussion

aldennX

Aug 6, 2023

ERROR:Failed to load the model.
Traceback (most recent call last):
File "C:\Users\Administrator\text-generation-webui\server.py", line 68, in load_model_wrapper
shared.model, shared.tokenizer = load_model(shared.model_name, loader)
File "C:\Users\Administrator\text-generation-webui\modules\models.py", line 78, in load_model
output = load_func_maploader
File "C:\Users\Administrator\text-generation-webui\modules\models.py", line 232, in llamacpp_loader
from modules.llamacpp_model import LlamaCppModel
File "C:\Users\Administrator\text-generation-webui\modules\llamacpp_model.py", line 11, in
import llama_cpp
File "C:\Users\Administrator.conda\envs\textgen\lib\site-packages\llama_cpp_init_.py", line 1, in
from .llama_cpp import *
File "C:\Users\Administrator.conda\envs\textgen\lib\site-packages\llama_cpp\llama_cpp.py", line 1292, in
llama_backend_init(c_bool(False))
File "C:\Users\Administrator.conda\envs\textgen\lib\site-packages\llama_cpp\llama_cpp.py", line 403, in llama_backend_init
return _lib.llama_backend_init(numa)
OSError: [WinError -1073741795] Windows Error 0xc000001d

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