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---
tags:
- merge
- mergekit
- lazymergekit
- datatab/Serbian-Mistral-Orca-Slim-v1
- mlabonne/AlphaMonarch-7B
- datatab/YugoGPT-Alpaca-v1-epoch1-good
base_model:
- datatab/Serbian-Mistral-Orca-Slim-v1
- mlabonne/AlphaMonarch-7B
- datatab/YugoGPT-Alpaca-v1-epoch1-good
---
# datatab/Serbian-Mistral-Orca-Slim-v1
datatab/Serbian-Mistral-Orca-Slim-v1 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [datatab/Serbian-Mistral-Orca-Slim-v1](https://huggingface.co/datatab/Serbian-Mistral-Orca-Slim-v1)
* [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B)
* [datatab/YugoGPT-Alpaca-v1-epoch1-good](https://huggingface.co/datatab/YugoGPT-Alpaca-v1-epoch1-good)
## 🧩 Configuration
```yaml
models:
- model: datatab/Serbian-Mistral-Orca-Slim-v1
parameters:
weight: 1.0
- model: mlabonne/AlphaMonarch-7B
parameters:
weight: 1.0
- model: datatab/YugoGPT-Alpaca-v1-epoch1-good
parameters:
weight: 1.0
merge_method: linear
dtype: float16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "datatab/datatab/Serbian-Mistral-Orca-Slim-v1"
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"])
``` |