How to use from
SGLangUse 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 "lilmeaty/abcdef" \
--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": "lilmeaty/abcdef",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'Quick Links
merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the passthrough merge method.
Models Merged
The following models were included in the merge:
- ICEPVP8977/Uncensored_llama_3.2_3b_safetensors
- ministral/Ministral-3b-instruct
- stabilityai/stable-code-3b
- PJMixers-Dev/LLaMa-3.2-Instruct-JankMix-v0.1-SFT-3B
- Bllossom/llama-3.2-Korean-Bllossom-3B
- chuanli11/Llama-3.2-3B-Instruct-uncensored
- Qwen/Qwen2.5-3B-Instruct
- meta-llama/Llama-3.2-3B-Instruct
- ibm-granite/granite-3b-code-base-2k
- Qwen/Qwen2.5-3B
- meta-llama/Llama-3.2-3B
Configuration
The following YAML configuration was used to produce this model:
slices:
- sources:
- layer_range: [0, 1]
model: ICEPVP8977/Uncensored_llama_3.2_3b_safetensors
- sources:
- layer_range: [0, 1]
model: meta-llama/Llama-3.2-3B-Instruct
- sources:
- layer_range: [0, 1]
model: meta-llama/Llama-3.2-3B
- sources:
- layer_range: [0, 1]
model: chuanli11/Llama-3.2-3B-Instruct-uncensored
- sources:
- layer_range: [0, 1]
model: PJMixers-Dev/LLaMa-3.2-Instruct-JankMix-v0.1-SFT-3B
- sources:
- layer_range: [0, 1]
model: Bllossom/llama-3.2-Korean-Bllossom-3B
- sources:
- layer_range: [0, 1]
model: Qwen/Qwen2.5-3B-Instruct
- sources:
- layer_range: [0, 1]
model: Qwen/Qwen2.5-3B
- sources:
- layer_range: [0, 1]
model: stabilityai/stable-code-3b
- sources:
- layer_range: [0, 1]
model: ibm-granite/granite-3b-code-base-2k
- sources:
- layer_range: [0, 2]
model: ministral/Ministral-3b-instruct
merge_method: passthrough
dtype: float16
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Install from pip and serve model
# Install SGLang from pip: pip install sglang# Start the SGLang server: python3 -m sglang.launch_server \ --model-path "lilmeaty/abcdef" \ --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": "lilmeaty/abcdef", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'