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---
base_model:
- S-miguel/The-Trinity-Coder-7B
- powermove72/Shark-1
tags:
- merge
- mergekit
- lazymergekit
- S-miguel/The-Trinity-Coder-7B
- powermove72/Shark-1
---
# IceShark-Coder-9b
IceShark-Coder-9b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [S-miguel/The-Trinity-Coder-7B](https://huggingface.co/S-miguel/The-Trinity-Coder-7B)
* [powermove72/Shark-1](https://huggingface.co/powermove72/Shark-1)
## 🧩 Configuration
```yaml
slices:
- sources:
- model: S-miguel/The-Trinity-Coder-7B
layer_range: [0, 16]
- sources:
- model: powermove72/Shark-1
layer_range: [8, 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/IceShark-Coder-9b"
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"])
``` |