Instructions to use kirikir13/MOEmoe-3x7B-BF16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use kirikir13/MOEmoe-3x7B-BF16 with Transformers:

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

pipe = pipeline("text-generation", model="kirikir13/MOEmoe-3x7B-BF16")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("kirikir13/MOEmoe-3x7B-BF16")
model = AutoModelForCausalLM.from_pretrained("kirikir13/MOEmoe-3x7B-BF16", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use kirikir13/MOEmoe-3x7B-BF16 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "kirikir13/MOEmoe-3x7B-BF16"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "kirikir13/MOEmoe-3x7B-BF16",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/kirikir13/MOEmoe-3x7B-BF16

SGLang

How to use kirikir13/MOEmoe-3x7B-BF16 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 "kirikir13/MOEmoe-3x7B-BF16" \
    --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": "kirikir13/MOEmoe-3x7B-BF16",
		"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 "kirikir13/MOEmoe-3x7B-BF16" \
        --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": "kirikir13/MOEmoe-3x7B-BF16",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use kirikir13/MOEmoe-3x7B-BF16 with Docker Model Runner:
```
docker model run hf.co/kirikir13/MOEmoe-3x7B-BF16
```

MOEmoe-3x7B-BF16

Architecture: Built from 3 models: [M] MixtralForCausalLM (model_type: mixtral), 1 expert [MINSTRAL] Minstrel Is Lee personality and tool department followed by [O] `openchat/openchat-3.5 Whose role is the logic and reasoning, Proceeded by:[E] openbmb/Eurus-7b-kto Who is head of the math department for a total of a 19B M.O.E. Named: "MOEmoe" Which is my very first M.O.E. Or as I like to say: "Mistral of Exports 😎. Next I will then be creating a couple of this in new specialized custom quants thus reducing it down to an estimated 7GB With your loss intelligence or abilities Stay tuned

Goerge Roby & 'theCREW' [DR Studios]

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