File size: 2,079 Bytes
cfaa161 676ada7 cfaa161 b26a811 cfaa161 |
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 |
---
tags:
- merge
- mergekit
- lazymergekit
- Kaoeiri/L3MaidRPKraiKei-V1.6-8B
- openlynn/Llama-3-Soliloquy-8B-v2
- Sao10K/L3-8B-Stheno-v3.2
base_model:
- Kaoeiri/L3MaidRPKraiKei-V1.6-8B
- openlynn/Llama-3-Soliloquy-8B-v2
- Sao10K/L3-8B-Stheno-v3.2
---
# L3MaidRPKraiKei-V1.65-8B
L3MaidRPKraiKei-V1.65-8B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
<img src="https://i.forfun.com/lx279qst.png" style="width: 80%; min-width: 400px; display: block; margin: left;">
# Keep in mind that, this merged model isn't usually tested at the moment, which could benefit in vocabulary error.
* [Kaoeiri/L3MaidRPKraiKei-V1.6-8B](https://huggingface.co/Kaoeiri/L3MaidRPKraiKei-V1.6-8B)
* [openlynn/Llama-3-Soliloquy-8B-v2](https://huggingface.co/openlynn/Llama-3-Soliloquy-8B-v2)
* [Sao10K/L3-8B-Stheno-v3.2](https://huggingface.co/Sao10K/L3-8B-Stheno-v3.2)
## 🧩 Configuration
```yaml
models:
- model: Kaoeiri/L3MaidRPKraiKei-V1.6-8B
parameters:
density: .5
weight: 1
- model: openlynn/Llama-3-Soliloquy-8B-v2
parameters:
density: .35
weight: .4
- model: Sao10K/L3-8B-Stheno-v3.2
parameters:
density: .5
weight: .7
merge_method: ties
base_model: mlabonne/NeuralDaredevil-8B-abliterated
parameters:
normalize: true
int8_mask: true
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Kaoeiri/L3MaidRPKraiKei-V1.65-8B"
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"])
``` |