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 Settings

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
```

Update model card to know the diffrence between (random) and (hidden) models

by rombodawg - opened Mar 15, 2024

Discussion

rombodawg

Mar 15, 2024

These two models have identical model cards, i have no idea what are the diffrences. Can you please update the model cards so people know which one is the version we are suppose to use for training. And what the main diffrences are

https://huggingface.co/Crystalcareai/GemMoE-Base-Random
https://huggingface.co/Crystalcareai/GemMoE-Base-Hidden

rombodawg

Mar 15, 2024

Ok i need to read lol for those of you who also didnt read just look at the howto.md for more details on the models

https://huggingface.co/Crystalcareai/GemMoE-Base-Random/blob/main/howto.md

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