Instructions to use tomg-group-umd/zero-model-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tomg-group-umd/zero-model-checkpoints with Transformers:

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

pipe = pipeline("image-text-to-text", model="tomg-group-umd/zero-model-checkpoints")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("tomg-group-umd/zero-model-checkpoints", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use tomg-group-umd/zero-model-checkpoints with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/tomg-group-umd/zero-model-checkpoints

SGLang

How to use tomg-group-umd/zero-model-checkpoints 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 "tomg-group-umd/zero-model-checkpoints" \
    --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": "tomg-group-umd/zero-model-checkpoints",
		"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 "tomg-group-umd/zero-model-checkpoints" \
        --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": "tomg-group-umd/zero-model-checkpoints",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use tomg-group-umd/zero-model-checkpoints with Docker Model Runner:
```
docker model run hf.co/tomg-group-umd/zero-model-checkpoints
```

kaiyuyue commited on May 21, 2025

Commit

badb792

verified ·

1 Parent(s): 9722c7a

update license

Browse files

Files changed (1) hide show

README.md +2 -3

README.md CHANGED Viewed

@@ -1,10 +1,9 @@
 ---
-license: mit
 base_model:
 - meta-llama/Llama-3.2-3B-Instruct
 - meta-llama/Llama-3.1-8B-Instruct
 - meta-llama/Llama-3.1-70B-Instruct
 - openai/clip-vit-large-patch14
 library_name: transformers
----

 ---
+license: cc
 base_model:
 - meta-llama/Llama-3.2-3B-Instruct
 - meta-llama/Llama-3.1-8B-Instruct
 - meta-llama/Llama-3.1-70B-Instruct
 - openai/clip-vit-large-patch14
 library_name: transformers
+---