File size: 2,205 Bytes
f1f7fb1 40740a9 f1f7fb1 40740a9 f1f7fb1 b3a8da2 f1f7fb1 3dcfec7 |
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 73 74 75 76 77 78 79 80 81 |
---
tags:
- merge
- mergekit
- lazymergekit
- Kukedlc/NeuralSirKrishna-7b
- Kukedlc/NeuralKybalion-7B-slerp-v3
- Kukedlc/SuperMente-7B-v3
base_model:
- Kukedlc/NeuralSirKrishna-7b
- Kukedlc/NeuralKybalion-7B-slerp-v3
- Kukedlc/SuperMente-7B-v3
license: apache-2.0
---
# SuperMente-7B-v4
SuperMente-7B-v4 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Kukedlc/NeuralSirKrishna-7b](https://huggingface.co/Kukedlc/NeuralSirKrishna-7b)
* [Kukedlc/NeuralKybalion-7B-slerp-v3](https://huggingface.co/Kukedlc/NeuralKybalion-7B-slerp-v3)
* [Kukedlc/SuperMente-7B-v3](https://huggingface.co/Kukedlc/SuperMente-7B-v3)
## 🧩 Configuration
```yaml
models:
- model: Kukedlc/NeuralSirKrishna-7b
parameters:
density: [1, 0.7, 0.1] # density gradient
weight: 1.0
- model: Kukedlc/NeuralKybalion-7B-slerp-v3
parameters:
density: 0.5
weight: [0, 0.3, 0.7, 1] # weight gradient
- model: Kukedlc/SuperMente-7B-v3
parameters:
density: 0.33
weight:
- filter: mlp
value: 0.5
- value: 0
merge_method: ties
base_model: Kukedlc/NeuralSirKrishna-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/SuperMente-7B-v4"
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"])
```
## Model Family
|