Instructions to use posterllava/posterllava_v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use posterllava/posterllava_v0 with Transformers:

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

pipe = pipeline("text-generation", model="posterllava/posterllava_v0")

# Load model directly
from transformers import AutoProcessor, AutoModelForCausalLM

processor = AutoProcessor.from_pretrained("posterllava/posterllava_v0")
model = AutoModelForCausalLM.from_pretrained("posterllava/posterllava_v0", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use posterllava/posterllava_v0 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "posterllava/posterllava_v0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "posterllava/posterllava_v0",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/posterllava/posterllava_v0

SGLang

How to use posterllava/posterllava_v0 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 "posterllava/posterllava_v0" \
    --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": "posterllava/posterllava_v0",
		"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 "posterllava/posterllava_v0" \
        --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": "posterllava/posterllava_v0",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use posterllava/posterllava_v0 with Docker Model Runner:
```
docker model run hf.co/posterllava/posterllava_v0
```

Add paper link to connect the model to the paper on Daily Papers page

by AdinaY HF Staff - opened Jun 6, 2024

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

-1

Files changed (1) hide show

README.md +4 -1

README.md CHANGED Viewed

@@ -21,4 +21,7 @@ posterllava_v0 was trained in March 2024.
 - 4k social media poster layouts from QB-Poster dataset
 ## Evaluation dataset
-the combination of the corresponding test sets of the above training datasets

 - 4k social media poster layouts from QB-Poster dataset
 ## Evaluation dataset
+the combination of the corresponding test sets of the above training datasets
+**Paper:**
+arxiv.org/abs/2406.02884