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---
base_model:
- Quazim0t0/time-14b-stock
- Quazim0t0/Mithril-14B-sce
tags:
- merge
- mergekit
- lazymergekit
- Quazim0t0/time-14b-stock
- Quazim0t0/Mithril-14B-sce
---
# Rosemary-14b
Rosemary-14b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Quazim0t0/time-14b-stock](https://huggingface.co/Quazim0t0/time-14b-stock)
* [Quazim0t0/Mithril-14B-sce](https://huggingface.co/Quazim0t0/Mithril-14B-sce)
## 🧩 Configuration
```yaml
base_model: Quazim0t0/time-14b-stock
dtype: bfloat16
merge_method: slerp
parameters:
t:
- filter: self_attn
value: [0.0, 0.5, 0.3, 0.7, 1.0]
- filter: mlp
value: [1.0, 0.5, 0.7, 0.3, 0.0]
- value: 0.5
slices:
- sources:
- layer_range: [0, 40]
model: Quazim0t0/time-14b-stock
- layer_range: [0, 40]
model: Quazim0t0/Mithril-14B-sce
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Quazim0t0/Rosemary-14b"
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"])
``` |