File size: 1,859 Bytes
96a2aea |
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 68 69 70 71 72 |
---
tags:
- merge
- mergekit
- lazymergekit
- Kukedlc/Neural4gsm8k
- PetroGPT/WestSeverus-7B-DPO
- samir-fama/FernandoGPT-v1
base_model:
- Kukedlc/Neural4gsm8k
- PetroGPT/WestSeverus-7B-DPO
- samir-fama/FernandoGPT-v1
---
# NeuralMaths-7B-slerp
NeuralMaths-7B-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Kukedlc/Neural4gsm8k](https://huggingface.co/Kukedlc/Neural4gsm8k)
* [PetroGPT/WestSeverus-7B-DPO](https://huggingface.co/PetroGPT/WestSeverus-7B-DPO)
* [samir-fama/FernandoGPT-v1](https://huggingface.co/samir-fama/FernandoGPT-v1)
## 🧩 Configuration
```yaml
models:
- model: Kukedlc/Neural4gsm8k
parameters:
density: [1, 0.7, 0.1] # density gradient
weight: 1.0
- model: PetroGPT/WestSeverus-7B-DPO
parameters:
density: 0.5
weight: [0, 0.3, 0.7, 1] # weight gradient
- model: samir-fama/FernandoGPT-v1
parameters:
density: 0.33
weight:
- filter: mlp
value: 0.5
- value: 0
merge_method: ties
base_model: liminerity/M7-7b
parameters:
normalize: true
int8_mask: true
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Kukedlc/NeuralMaths-7B-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"])
``` |