File size: 1,756 Bytes
9f1b647
 
 
 
 
 
 
 
 
 
0468ff6
9f1b647
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
---
tags:
- merge
- mergekit
- lazymergekit
- eren23/ogno-monarch-jaskier-merge-7b
- mlabonne/AlphaMonarch-7B
base_model:
- eren23/ogno-monarch-jaskier-merge-7b
- mlabonne/AlphaMonarch-7B
license: cc-by-nc-4.0
---

# ogno-monarch-jaskier-merge-7b-v2

ogno-monarch-jaskier-merge-7b-v2 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [eren23/ogno-monarch-jaskier-merge-7b](https://huggingface.co/eren23/ogno-monarch-jaskier-merge-7b)
* [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B)

## 🧩 Configuration

```yaml
models:
  - model: eren23/dpo-binarized-NeutrixOmnibe-7B
    # No parameters necessary for base model
  - model: eren23/ogno-monarch-jaskier-merge-7b
    parameters:
      weight: 0.7
      density: 0.6
  - model: mlabonne/AlphaMonarch-7B
    parameters:
      weight: 0.3
      density: 0.45


merge_method: dare_ties
base_model: eren23/dpo-binarized-NeutrixOmnibe-7B
parameters:
  int8_mask: true
dtype: bfloat16
random_seed: 0
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "eren23/ogno-monarch-jaskier-merge-7b-v2"
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"])
```