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---
base_model:
- GritLM/GritLM-7B
- jan-hq/trinity-v1
- GreenNode/GreenNode-mini-7B-multilingual-v1olet
tags:
- merge
- mergekit
- lazymergekit
- GritLM/GritLM-7B
- jan-hq/trinity-v1
- GreenNode/GreenNode-mini-7B-multilingual-v1olet
---
# Shark-1.1
Shark-1.1 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [GritLM/GritLM-7B](https://huggingface.co/GritLM/GritLM-7B)
* [jan-hq/trinity-v1](https://huggingface.co/jan-hq/trinity-v1)
* [GreenNode/GreenNode-mini-7B-multilingual-v1olet](https://huggingface.co/GreenNode/GreenNode-mini-7B-multilingual-v1olet)
## 🧩 Configuration
```yaml
slices:
- sources:
- model: GritLM/GritLM-7B
layer_range: [0, 8]
- sources:
- model: jan-hq/trinity-v1
layer_range: [8, 20]
- sources:
- model: GreenNode/GreenNode-mini-7B-multilingual-v1olet
layer_range: [20, 32]
merge_method: passthrough
tokenizer_source: union
dtype: float16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "powermove72/Shark-1.1"
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"])
``` |