Text Generation
Transformers
Safetensors
mistral
Merge
mergekit
lazymergekit
RJuro/munin-neuralbeagle-7b
timpal0l/BeagleCatMunin
macadeliccc/WestLake-7B-v2-laser-truthy-dpo
bineric/NorskGPT-Mistral-7b
meta-math/MetaMath-Mistral-7B
teknium/OpenHermes-2.5-Mistral-7B
text-generation-inference
Inference Endpoints
File size: 2,698 Bytes
1967187 |
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 82 83 84 85 86 87 88 89 |
---
tags:
- merge
- mergekit
- lazymergekit
- RJuro/munin-neuralbeagle-7b
- timpal0l/BeagleCatMunin
- macadeliccc/WestLake-7B-v2-laser-truthy-dpo
- bineric/NorskGPT-Mistral-7b
- meta-math/MetaMath-Mistral-7B
- teknium/OpenHermes-2.5-Mistral-7B
base_model:
- RJuro/munin-neuralbeagle-7b
- timpal0l/BeagleCatMunin
- macadeliccc/WestLake-7B-v2-laser-truthy-dpo
- bineric/NorskGPT-Mistral-7b
- meta-math/MetaMath-Mistral-7B
- teknium/OpenHermes-2.5-Mistral-7B
---
# WestLake-Munin-Cat-NorskGPT
WestLake-Munin-Cat-NorskGPT is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [RJuro/munin-neuralbeagle-7b](https://huggingface.co/RJuro/munin-neuralbeagle-7b)
* [timpal0l/BeagleCatMunin](https://huggingface.co/timpal0l/BeagleCatMunin)
* [macadeliccc/WestLake-7B-v2-laser-truthy-dpo](https://huggingface.co/macadeliccc/WestLake-7B-v2-laser-truthy-dpo)
* [bineric/NorskGPT-Mistral-7b](https://huggingface.co/bineric/NorskGPT-Mistral-7b)
* [meta-math/MetaMath-Mistral-7B](https://huggingface.co/meta-math/MetaMath-Mistral-7B)
* [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B)
## 🧩 Configuration
```yaml
models:
- model: RJuro/munin-neuralbeagle-7b
parameters:
density: 0.53
weight: 0.2
- model: timpal0l/BeagleCatMunin
parameters:
density: 0.53
weight: 0.2
- model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo
parameters:
density: 0.53
weight: 0.2
- model: bineric/NorskGPT-Mistral-7b
parameters:
density: 0.53
weight: 0.2
- model: meta-math/MetaMath-Mistral-7B
parameters:
density: 0.53
weight: 0.1
- model: teknium/OpenHermes-2.5-Mistral-7B
parameters:
density: 0.53
weight: 0.1
merge_method: dare_ties
base_model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo
parameters:
int8_mask: true
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "birgermoell/WestLake-Munin-Cat-NorskGPT"
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"])
``` |