Text Generation
Safetensors
English
qwen3
gptqmodel
modelcloud
chat
marin
instruct
int4
awq
4bit
w4a16
4-bit precision
Instructions to use ModelCloud/Marin-32B-Base-GPTQMODEL-AWQ-W4A16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- vLLM
How to use ModelCloud/Marin-32B-Base-GPTQMODEL-AWQ-W4A16 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ModelCloud/Marin-32B-Base-GPTQMODEL-AWQ-W4A16" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ModelCloud/Marin-32B-Base-GPTQMODEL-AWQ-W4A16", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ModelCloud/Marin-32B-Base-GPTQMODEL-AWQ-W4A16
- SGLang
How to use ModelCloud/Marin-32B-Base-GPTQMODEL-AWQ-W4A16 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 "ModelCloud/Marin-32B-Base-GPTQMODEL-AWQ-W4A16" \ --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": "ModelCloud/Marin-32B-Base-GPTQMODEL-AWQ-W4A16", "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 "ModelCloud/Marin-32B-Base-GPTQMODEL-AWQ-W4A16" \ --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": "ModelCloud/Marin-32B-Base-GPTQMODEL-AWQ-W4A16", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ModelCloud/Marin-32B-Base-GPTQMODEL-AWQ-W4A16 with Docker Model Runner:
docker model run hf.co/ModelCloud/Marin-32B-Base-GPTQMODEL-AWQ-W4A16
| { | |
| "bits": 4, | |
| "group_size": 32, | |
| "desc_act": false, | |
| "sym": true, | |
| "lm_head": false, | |
| "quant_method": "awq", | |
| "checkpoint_format": "gemm", | |
| "pack_dtype": "int32", | |
| "meta": { | |
| "quantizer": [ | |
| "gptqmodel:5.1.0-dev" | |
| ], | |
| "uri": "https://github.com/modelcloud/gptqmodel", | |
| "damp_percent": 0.05, | |
| "damp_auto_increment": 0.01, | |
| "static_groups": false, | |
| "true_sequential": true, | |
| "mse": 0.0, | |
| "v2": false, | |
| "v2_alpha": 0.25, | |
| "act_group_aware": true | |
| }, | |
| "pack_impl": "cpu", | |
| "zero_point": true, | |
| "version": "gemm" | |
| } |