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---
tags:
- merge
- mergekit
- kasper52786/StoryWeaver-7b-Instruct-v0.1
- N8Programs/Coxcomb
- Norquinal/Mistral-7B-storywriter
base_model:
- kasper52786/StoryWeaver-7b-Instruct-v0.1
- N8Programs/Coxcomb
- Norquinal/Mistral-7B-storywriter
---
# StoryFusion-7B
StoryFusion-7B is a merge of the following models:
* [kasper52786/StoryWeaver-7b-Instruct-v0.1](https://huggingface.co/kasper52786/StoryWeaver-7b-Instruct-v0.1)
* [N8Programs/Coxcomb](https://huggingface.co/N8Programs/Coxcomb)
* [Norquinal/Mistral-7B-storywriter](https://huggingface.co/Norquinal/Mistral-7B-storywriter)
## 🧩 Configuration
```yaml
models:
- model: senseable/WestLake-7B-v2
# No parameters necessary for base model
- model: kasper52786/StoryWeaver-7b-Instruct-v0.1
parameters:
density: 0.53
weight: 0.4
- model: N8Programs/Coxcomb
parameters:
density: 0.53
weight: 0.3
- model: Norquinal/Mistral-7B-storywriter
parameters:
density: 0.53
weight: 0.3
merge_method: dare_ties
base_model: senseable/WestLake-7B-v2
parameters:
int8_mask: true
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "OmnicromsBrain/StoryFusion-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"])
``` |