---
language:
- en
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- meta-llama/Meta-Llama-3-8B
- beratcmn/Llama-3-11.5B
- text-generation-inference
- transformers
- unsloth
- llama
- trl
base_model: beratcmn/Llama-3-11.5B
---
# Llama-3-11.5B

This model is a Proof of Concept. First 2 Llama-3-8B models has been merged using `Mergekit` and pre-training continued using `QLora` and `Unsloth` for 1000 samples from `roneneldan/TinyStories`.
Loss still decreases each epoch so I believe this is a successful experiment where there is a lot of room to experiment. 

[Wandb Report](https://wandb.ai/beratcmn/huggingface/reports/beratcmn-Llama-3-11-5B-v0-1--Vmlldzo3NjUzMTgx)

Llama-3-11.5B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B)
* [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B)

## 🧩 Configuration

```yaml
slices:
  - sources:
    - model: meta-llama/Meta-Llama-3-8B
      layer_range: [0, 24]
  - sources:
    - model: meta-llama/Meta-Llama-3-8B
      layer_range: [8, 32]
merge_method: passthrough
dtype: bfloat16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "beratcmn/Llama-3-11.5B"
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"])
```

# Uploaded  model

- **Developed by:** beratcmn
- **License:** apache-2.0
- **Finetuned from model :** beratcmn/Llama-3-11.5B

This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.

[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)