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 Settings

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
```

Hardware Requirement for the model to run in LORA

#14

by Leo4sho - opened Oct 21, 2024

Discussion

Leo4sho

Oct 21, 2024

I would like to know the minimum GPU memory requirements needed to effectively run this model in a LoRA setup.

Could anyone share their experiences or insights regarding the necessary GPU memory for this configuration? Any recommendations would be greatly appreciated!

Thank you!

stockfish7

13 days ago

•

edited 13 days ago

I would like to know the minimum GPU memory requirements needed to effectively run this model in a LoRA setup.

Could anyone share their experiences or insights regarding the necessary GPU memory for this configuration? Any recommendations would be greatly appreciated!

Thank you!

i tested this on rtx 3050 4gb and 16gigs ram it i5 12500h cpu, worked well but my machine heated up way too quick, 7B makes sense
you can set frames number around 5-7 depending upon your gpu else your vram will explode

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