Instructions to use gagan3012/MetaModel_moe_multilingualv1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use gagan3012/MetaModel_moe_multilingualv1 with Transformers:

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

pipe = pipeline("text-generation", model="gagan3012/MetaModel_moe_multilingualv1")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("gagan3012/MetaModel_moe_multilingualv1")
model = AutoModelForCausalLM.from_pretrained("gagan3012/MetaModel_moe_multilingualv1")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use gagan3012/MetaModel_moe_multilingualv1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "gagan3012/MetaModel_moe_multilingualv1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "gagan3012/MetaModel_moe_multilingualv1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/gagan3012/MetaModel_moe_multilingualv1

SGLang

How to use gagan3012/MetaModel_moe_multilingualv1 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 "gagan3012/MetaModel_moe_multilingualv1" \
    --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": "gagan3012/MetaModel_moe_multilingualv1",
		"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 "gagan3012/MetaModel_moe_multilingualv1" \
        --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": "gagan3012/MetaModel_moe_multilingualv1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use gagan3012/MetaModel_moe_multilingualv1 with Docker Model Runner:
```
docker model run hf.co/gagan3012/MetaModel_moe_multilingualv1
```

gagan3012 commited on Jan 7, 2024

Commit

1b27a5a

1 Parent(s): f275386

Update README.md

Browse files

Files changed (1) hide show

README.md +7 -14

README.md CHANGED Viewed

@@ -4,20 +4,13 @@ tags:
 - moe
 - mergekit
 - merge
-- chinese
-- arabic
-- english
-- multilingual
-- german
-- french
-- openchat/openchat-3.5-1210
-- beowolx/CodeNinja-1.0-OpenChat-7B
-- maywell/PiVoT-0.1-Starling-LM-RP
-- WizardLM/WizardMath-7B-V1.1
-- davidkim205/komt-mistral-7b-v1
-- OpenBuddy/openbuddy-zephyr-7b-v14.1
-- manishiitg/open-aditi-hi-v1
-- VAGOsolutions/SauerkrautLM-7b-v1-mistral
 ---
 # MetaModel_moe_multilingualv1

 - moe
 - mergekit
 - merge
+language:
+- en
+- hi
+- de
+- fr
+- ar
+- ja
 ---
 # MetaModel_moe_multilingualv1