Instructions to use LanguageBind/MoE-LLaVA-Qwen-1.8B-4e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LanguageBind/MoE-LLaVA-Qwen-1.8B-4e with Transformers:

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

pipe = pipeline("text-generation", model="LanguageBind/MoE-LLaVA-Qwen-1.8B-4e", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("LanguageBind/MoE-LLaVA-Qwen-1.8B-4e", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use LanguageBind/MoE-LLaVA-Qwen-1.8B-4e with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LanguageBind/MoE-LLaVA-Qwen-1.8B-4e"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LanguageBind/MoE-LLaVA-Qwen-1.8B-4e",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/LanguageBind/MoE-LLaVA-Qwen-1.8B-4e

SGLang

How to use LanguageBind/MoE-LLaVA-Qwen-1.8B-4e 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/MoE-LLaVA-Qwen-1.8B-4e" \
    --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/MoE-LLaVA-Qwen-1.8B-4e",
		"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/MoE-LLaVA-Qwen-1.8B-4e" \
        --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/MoE-LLaVA-Qwen-1.8B-4e",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use LanguageBind/MoE-LLaVA-Qwen-1.8B-4e with Docker Model Runner:
```
docker model run hf.co/LanguageBind/MoE-LLaVA-Qwen-1.8B-4e
```

ModuleNotFoundError: No module named 'mpi4py'

by Andyrasika - opened Feb 1, 2024

Discussion

Andyrasika

Feb 1, 2024

I tried

python -m pip install git+https://github.com/mpi4py/mpi4py

but got error:

      _configtest.c:2:10: fatal error: mpi.h: No such file or directory
          2 | #include <mpi.h>
            |          ^~~~~~~
      compilation terminated.
      failure.
      removing: _configtest.c _configtest.o
      error: Cannot compile MPI programs. Check your configuration!!!
      Installing mpi4py requires a working MPI implementation.
      If you are running on a supercomputer or cluster, check with
      the system administrator or refer to the system user guide.
      Otherwise, if you are running on a laptop or desktop computer,
      your may be missing the MPICH or Open MPI development package:
      * On Fedora/RHEL systems, run:
        $ sudo dnf install mpich-devel     # for MPICH
        $ sudo dnf install openmpi-devel   # for Open MPI
      * On Debian/Ubuntu systems, run:
        $ sudo apt install libmpich-dev    # for MPICH
        $ sudo apt install libopenmpi-dev  # for Open MPI
      [end of output]
  
  note: This error originates from a subprocess, and is likely not a problem with pip.
  ERROR: Failed building wheel for mpi4py
Failed to build mpi4py
ERROR: Could not build wheels for mpi4py, which is required to install pyproject.toml-based projects

zhongyi1997cn

Mar 19, 2024

•

edited Mar 19, 2024

use command

deepspeed predict.py

then it works

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