Instructions to use LanguageBind/Video-LLaVA-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LanguageBind/Video-LLaVA-7B with Transformers:

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

pipe = pipeline("text-generation", model="LanguageBind/Video-LLaVA-7B")

# Load model directly
from transformers import AutoProcessor, AutoModelForCausalLM

processor = AutoProcessor.from_pretrained("LanguageBind/Video-LLaVA-7B")
model = AutoModelForCausalLM.from_pretrained("LanguageBind/Video-LLaVA-7B")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use LanguageBind/Video-LLaVA-7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LanguageBind/Video-LLaVA-7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LanguageBind/Video-LLaVA-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/LanguageBind/Video-LLaVA-7B

SGLang

How to use LanguageBind/Video-LLaVA-7B 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 "LanguageBind/Video-LLaVA-7B" \
    --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": "LanguageBind/Video-LLaVA-7B",
		"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 "LanguageBind/Video-LLaVA-7B" \
        --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": "LanguageBind/Video-LLaVA-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use LanguageBind/Video-LLaVA-7B with Docker Model Runner:
```
docker model run hf.co/LanguageBind/Video-LLaVA-7B
```

LanguageBind

SFconvertbot commited on Apr 9, 2024

Commit

aecae02

verified ·

1 Parent(s): b1d6a63

Adding `safetensors` variant of this model (#8)

Browse files

- Adding `safetensors` variant of this model (3817317315a16bd40e8d8f4c494043a5512227e7)

Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>

Files changed (3) hide show

model-00001-of-00002.safetensors +3 -0
model-00002-of-00002.safetensors +3 -0
model.safetensors.index.json +0 -0

model-00001-of-00002.safetensors ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:0e342ae2c6d40d6ebba3328904310a00a2b82e57c728e0e4f5059fe6f7774a03
+size 9976576392

model-00002-of-00002.safetensors ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:fb5c47457569d61be0d2b2d5739f1e30985acc5a61160406880fee64d2c8e111
+size 4957139888

model.safetensors.index.json ADDED Viewed

The diff for this file is too large to render. See raw diff