RolePlayLake-7B / README.md
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---
tags:
- merge
- mergekit
- mistral
- SanjiWatsuki/Silicon-Maid-7B
- senseable/WestLake-7B-v2
base_model:
- SanjiWatsuki/Silicon-Maid-7B
- senseable/WestLake-7B-v2
license: apache-2.0
---
# RolePlayLake-7B
RolePlayLake-7B is a merge of the following models :
* [SanjiWatsuki/Silicon-Maid-7B](https://huggingface.co/SanjiWatsuki/Silicon-Maid-7B)
* [senseable/WestLake-7B-v2](https://huggingface.co/senseable/WestLake-7B-v2)
## 🧩 Configuration
```yaml
slices:
- sources:
- model: SanjiWatsuki/Silicon-Maid-7B
layer_range: [0, 32]
- model: senseable/WestLake-7B-v2
layer_range: [0, 32]
merge_method: slerp
base_model: senseable/WestLake-7B-v2
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "fhai50032/RolePlayLake-7B"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```
# Why I Merged WestLake and Silicon Maid
Merged WestLake and Silicon Maid for a unique blend:
1. **EQ-Bench Dominance:** WestLake's 79.75 EQ-Bench score. (Maybe Contaminated)
2. **Charm and Role-Play:** Silicon's explicit charm and WestLake's role-play prowess.
3. **Config Synergy:** Supports lots of prompt format out of the gate and has a very nice synergy
Result: RolePlayLake-7B, a linguistic fusion with EQ-Bench supremacy and captivating role-play potential.