README.md

---
base_model:
- meta-llama/Meta-Llama-3-8B-Instruct
- rombodawg/Llama-3-8B-Instruct-Coder
tags:
- merge
- mergekit
- lazymergekit
- meta-llama/Meta-Llama-3-8B-Instruct
- rombodawg/Llama-3-8B-Instruct-Coder
---

# Llama3-CodeInstruct-8B

Llama3-CodeInstruct-8B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)
* [rombodawg/Llama-3-8B-Instruct-Coder](https://huggingface.co/rombodawg/Llama-3-8B-Instruct-Coder)

## 🧩 Configuration

```yaml
merge_method: dare_ties
base_model: meta-llama/Meta-Llama-3-8B-Instruct
models:
  - model: meta-llama/Meta-Llama-3-8B-Instruct
    parameters:
      weight: 0.45
      density: 0.6
  - model: rombodawg/Llama-3-8B-Instruct-Coder
    parameters:
      weight: 0.55
      density: 0.7
parameters:
  int8_mask: true
  normalize: true
dtype: bfloat16
tokenizer_source: meta-llama/Meta-Llama-3-8B-Instruct
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "AIencoder/Llama3-CodeInstruct-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"])
```