Instructions to use Crystalcareai/GemMoE-Base-Random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Crystalcareai/GemMoE-Base-Random with Transformers:

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

pipe = pipeline("text-generation", model="Crystalcareai/GemMoE-Base-Random", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Crystalcareai/GemMoE-Base-Random", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Crystalcareai/GemMoE-Base-Random with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/Crystalcareai/GemMoE-Base-Random

SGLang

How to use Crystalcareai/GemMoE-Base-Random 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 "Crystalcareai/GemMoE-Base-Random" \
    --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": "Crystalcareai/GemMoE-Base-Random",
		"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 "Crystalcareai/GemMoE-Base-Random" \
        --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": "Crystalcareai/GemMoE-Base-Random",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Crystalcareai/GemMoE-Base-Random with Docker Model Runner:
```
docker model run hf.co/Crystalcareai/GemMoE-Base-Random
```

Help

by damerajee - opened Mar 19, 2024

Discussion

damerajee

Mar 19, 2024

•

edited Mar 19, 2024

So I got inspired by you and I wanted to do something similar to this just for experimenting with it ,so I implemented Llamoe which is this model https://huggingface.co/damerajee/Llamoe-test , and I keep getting this error
RuntimeError: The size of tensor a (200) must match the size of tensor b (2048) at non-singleton dimension 3 can you fix this
So I look through your modeling code and it seems as if most of it is like similar to the Llama architecture ,so I copied mostly from your code but started changing stuff here and there , I really tried fixing the error , but this is the first time I'm coding a MOE model so any help please

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment