File size: 1,752 Bytes
7fb51e0
 
 
 
 
 
 
 
 
 
 
 
087c900
 
7fb51e0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
tags:
- merge
- mergekit
- lazymergekit
- KoboldAI/LLaMA2-13B-Tiefighter
- ddh0/OrcaMaid-v3-13b-32k
base_model:
- KoboldAI/LLaMA2-13B-Tiefighter
- ddh0/OrcaMaid-v3-13b-32k
---

02/05/2024: Fixed Vocab issues related to GGUF conversion.

# D_AU-Tiefighter-OrcaMaid-V3-13B-32k-slerp

D_AU-Tiefighter-OrcaMaid-V3-13B-32k-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [KoboldAI/LLaMA2-13B-Tiefighter](https://huggingface.co/KoboldAI/LLaMA2-13B-Tiefighter)
* [ddh0/OrcaMaid-v3-13b-32k](https://huggingface.co/ddh0/OrcaMaid-v3-13b-32k)

## 🧩 Configuration

```yaml
slices:
  - sources:
      - model: KoboldAI/LLaMA2-13B-Tiefighter
        layer_range: [0, 40]
      - model: ddh0/OrcaMaid-v3-13b-32k
        layer_range: [0, 40]
merge_method: slerp
base_model: ddh0/OrcaMaid-v3-13b-32k
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 = "DavidAU/D_AU-Tiefighter-OrcaMaid-V3-13B-32k-slerp"
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"])
```