How to use from the
Use from the
llama-cpp-python library
# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Aryanne/WestSenzu-Swap-7B",
	filename="",
)
output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

It's experimental, but seems fine for me, I didn't run it deeply yet but should be good for Role-play 😈 considering the two merged models, feel free to leave a suggestion or feedback.

This is a merge of pre-trained language models created using mergekit(my experimental branch swapping here )

Merge Details

Merge Method

This model was merged using the task_swapping merge method using NeuralNovel/Senzu-7B-v0.1-DPO as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

merge_method: task_swapping
base_model: NeuralNovel/Senzu-7B-v0.1-DPO
models:
  - model: senseable/WestLake-7B-v2
    parameters:
      weight: 0.75
      diagonal_offset: 2    #it doesn't do anything when you use random_mask
      random_mask: 0.3333
      random_mask_seed: 98557
dtype: bfloat16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 67.28
AI2 Reasoning Challenge (25-Shot) 68.34
HellaSwag (10-Shot) 85.70
MMLU (5-Shot) 64.14
TruthfulQA (0-shot) 50.43
Winogrande (5-shot) 82.48
GSM8k (5-shot) 52.62
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