Instructions to use OpenNLPLab/TransNormerLLM-385M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OpenNLPLab/TransNormerLLM-385M with Transformers:

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

pipe = pipeline("text-generation", model="OpenNLPLab/TransNormerLLM-385M", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("OpenNLPLab/TransNormerLLM-385M", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use OpenNLPLab/TransNormerLLM-385M with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "OpenNLPLab/TransNormerLLM-385M"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OpenNLPLab/TransNormerLLM-385M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/OpenNLPLab/TransNormerLLM-385M

SGLang

How to use OpenNLPLab/TransNormerLLM-385M 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 "OpenNLPLab/TransNormerLLM-385M" \
    --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": "OpenNLPLab/TransNormerLLM-385M",
		"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 "OpenNLPLab/TransNormerLLM-385M" \
        --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": "OpenNLPLab/TransNormerLLM-385M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use OpenNLPLab/TransNormerLLM-385M with Docker Model Runner:
```
docker model run hf.co/OpenNLPLab/TransNormerLLM-385M
```

OpenNLPLab commited on Oct 16, 2023

Commit

b0a3184

1 Parent(s): 9e58c9b

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@@ -15,7 +15,7 @@ tags:
 </div>
 <p align="center">
-🤗 <a href="https://github.com/OpenNLPLab/TransnormerLLM" target="_blank">GitHub </a> • 💬 <a href="https://discord.gg/W4Vr7AKW" target="_blank">Discord</a> • 💬 <a href="./images/contact_me_qr.png" target="_blank">Wechat</a>
 </p>
@@ -208,7 +208,7 @@ We hereby declare that our team has not developed any applications based on Tran
 We have done our best to ensure the compliance of the data used in the model training process. However, despite our considerable efforts, there may still be some unforeseeable issues due to the complexity of the model and data. Therefore, if any problems arise due to the use of TransNormerLLM open-source models, including but not limited to data security issues, public opinion risks, or any risks and problems brought about by the model being misled, abused, spread or improperly exploited, we will not assume any responsibility.
 ## License
-The community usage of TransNormerLLM model requires adherence to [Apache 2.0](https://github.com/OpenNLPLab/TransNormerLLM/blob/main/LICENSE) and [Community License for TransNormerLLM Model](https://huggingface.co/OpenNLPLab/TransNormerLLM-7B-Base/resolve/main/TransNormerLLM%202%E6%A8%A1%E5%9E%8B%E7%A4%BE%E5%8C%BA%E8%AE%B8%E5%8F%AF%E5%8D%8F%E8%AE%AE.pdf). The TransNormerLLM model supports commercial use. If you plan to use the TransNormerLLM model or its derivatives for commercial purposes, please ensure that your entity meets the following conditions:
   1. The Daily Active Users (DAU) of your or your affiliate's service or product is less than 1 million.
   2. Neither you nor your affiliates are software service providers or cloud service providers.

 </div>
 <p align="center">
+💻 <a href="https://github.com/OpenNLPLab/TransnormerLLM" target="_blank">GitHub </a> • 💬 <a href="https://discord.gg/W4Vr7AKW" target="_blank">Discord</a> • 💬 <a href="./images/contact_me_qr.png" target="_blank">Wechat</a>
 </p>
 We have done our best to ensure the compliance of the data used in the model training process. However, despite our considerable efforts, there may still be some unforeseeable issues due to the complexity of the model and data. Therefore, if any problems arise due to the use of TransNormerLLM open-source models, including but not limited to data security issues, public opinion risks, or any risks and problems brought about by the model being misled, abused, spread or improperly exploited, we will not assume any responsibility.
 ## License
+The community usage of TransNormerLLM model requires adherence to [Apache 2.0](https://github.com/OpenNLPLab/TransNormerLLM/blob/main/LICENSE) and [Community License for TransNormerLLM Model](https://huggingface.co/OpenNLPLab/TransNormerLLM-385M/blob/main/TransNormerLLM模型社区许可协议.pdf). The TransNormerLLM model supports commercial use. If you plan to use the TransNormerLLM model or its derivatives for commercial purposes, please ensure that your entity meets the following conditions:
   1. The Daily Active Users (DAU) of your or your affiliate's service or product is less than 1 million.
   2. Neither you nor your affiliates are software service providers or cloud service providers.