Resolving Interference When Merging Models
Paper • 2306.01708 • Published • 18
This is a merge of pre-trained language models created using mergekit.
This model was merged using the TIES merge method using appvoid/palmer-003 as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
models:
- model: vihangd/DopeyTinyLlama-1.1B-v1
parameters:
density: 0.5
weight: 0.5
- model: raidhon/coven_tiny_1.1b_32k_orpo_alpha
parameters:
density: 0.5
weight: 0.5
merge_method: ties
base_model: appvoid/palmer-003
parameters:
normalize: false
int8_mask: true
dtype: float16
Install from pip and serve model
# Install vLLM from pip: pip install vllm# Start the vLLM server: vllm serve "appvoid/v-base"# Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "appvoid/v-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'