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)

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

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
```

TransNormerLLM-385M

Commit History

Jan 27, 2025

18:32
Adding `safetensors` variant of this model⁠

SFconvertbot

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be0127c

Feb 26, 2024

03:39
Upgrade to lightning att2

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d88d1ec

Jan 26, 2024

09:45
Upload modeling_transnormer.py

OpenNLPLab

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c78a6f3

Nov 17, 2023

04:11
Fix issuse regarding to transformer version

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a706060

Nov 13, 2023

10:42
Update README.md

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dbdaec7

Oct 17, 2023

07:30
Update README.md

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1a0123b

Oct 16, 2023

13:22
Upload Community License for TransNormerLLM Model.pdf

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8f7e5c2
09:49
Update README.md

OpenNLPLab

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09:47
Upload TransNormerLLM模型社区许可协议.pdf

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08:44
Update README.md

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06:36
Update README.md

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Oct 15, 2023

03:58
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fc689fe
03:45
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8d3a720
03:19
Publish 385M Model

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e423fc2

Oct 14, 2023

16:59
Update README.md

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6f9cdf4
16:53
initial commit

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Commit History

Jan 27, 2025

Adding `safetensors` variant of this model⁠

Feb 26, 2024

Upgrade to lightning att2

Jan 26, 2024

Upload modeling_transnormer.py

Nov 17, 2023

Fix issuse regarding to transformer version

Nov 13, 2023

Update README.md

Oct 17, 2023

Update README.md

Oct 16, 2023

Upload Community License for TransNormerLLM Model.pdf

Update README.md

Upload TransNormerLLM模型社区许可协议.pdf

Update README.md

Update README.md

Oct 15, 2023

Update README.md

Update README.md

Update README.md

Update README.md

Publish 385M Model

Oct 14, 2023

Update README.md

initial commit