Resolving Interference When Merging Models
Paper • 2306.01708 • Published • 19
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 "appvoid/dot-test-1" \
--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": "appvoid/dot-test-1",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'This is a merge of pre-trained language models created using mergekit.
This model was merged using the TIES merge method using appvoid/palmer-004 as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
models:
- model: microsoft/rho-math-1b-v0.1
parameters:
density: 0.5
weight: 0.5
- model: Josephgflowers/TinyLlama-Cinder-Agent-v1
parameters:
density: 0.5
weight: 0.5
merge_method: ties
base_model: appvoid/palmer-004
parameters:
normalize: false
int8_mask: true
dtype: float16
Install from pip and serve model
# Install SGLang from pip: pip install sglang# Start the SGLang server: python3 -m sglang.launch_server \ --model-path "appvoid/dot-test-1" \ --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": "appvoid/dot-test-1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'