Instructions to use Skywork/Skywork-13B-Math-8bits with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Skywork/Skywork-13B-Math-8bits with Transformers:

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

pipe = pipeline("text-generation", model="Skywork/Skywork-13B-Math-8bits", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Skywork/Skywork-13B-Math-8bits", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Skywork/Skywork-13B-Math-8bits with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Skywork/Skywork-13B-Math-8bits"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Skywork/Skywork-13B-Math-8bits",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Skywork/Skywork-13B-Math-8bits

SGLang

How to use Skywork/Skywork-13B-Math-8bits 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 "Skywork/Skywork-13B-Math-8bits" \
    --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": "Skywork/Skywork-13B-Math-8bits",
		"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 "Skywork/Skywork-13B-Math-8bits" \
        --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": "Skywork/Skywork-13B-Math-8bits",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Skywork/Skywork-13B-Math-8bits with Docker Model Runner:
```
docker model run hf.co/Skywork/Skywork-13B-Math-8bits
```

zhao1iang commited on Oct 28, 2023

Commit

74cf438

1 Parent(s): 5615c8e

Update README.md

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@@ -233,7 +233,7 @@ model = AutoModelForCausalLM.from_pretrained("skywork-13B-Base-8bits", device_ma
 | Precision | C-Eval | MMLU  | CMMLU |
 | --------- | ------ | ----- | ----- |
-| bf16      | 59.5  | 61.6 | 61.6 |
 | 8bits     | 58.5  | 61.8 | 61.0 |
 ### 显存占用（GPU Mem in GB）
@@ -244,7 +244,6 @@ model = AutoModelForCausalLM.from_pretrained("skywork-13B-Base-8bits", device_ma
 | 8bits     | 13.57       |
 # 声明和协议（Declaration and License Aggrement）

 | Precision | C-Eval | MMLU  | CMMLU |
 | --------- | ------ | ----- | ----- |
+| bf16      | 60.6  | 61.8 | 62.1 |
 | 8bits     | 58.5  | 61.8 | 61.0 |
 ### 显存占用（GPU Mem in GB）
 | 8bits     | 13.57       |
 # 声明和协议（Declaration and License Aggrement）