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mlabonne_Meta-Llama-3-12B-Instruct-2_2bpw_exl2

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mlabonne_Meta-Llama-3-12B-Instruct-2_2bpw_exl2
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---
license: other
tags:
- merge
- mergekit
- lazymergekit
base_model:
- NousResearch/Meta-Llama-3-8B-Instruct
- NousResearch/Meta-Llama-3-8B-Instruct
- NousResearch/Meta-Llama-3-8B-Instruct
- NousResearch/Meta-Llama-3-8B-Instruct
- NousResearch/Meta-Llama-3-8B-Instruct
---
**Exllamav2** quant (**exl2** / **2.2 bpw**) made with ExLlamaV2 v0.0.21

Other EXL2 quants:
| **Quant** | **Model Size** | **lm_head** |
| ----- | ---------- | ------- |
|<center>**[2.2](https://huggingface.co/Zoyd/mlabonne_Meta-Llama-3-12B-Instruct-2_2bpw_exl2)**</center> | <center>4176 MB</center> | <center>6</center> |
|<center>**[2.5](https://huggingface.co/Zoyd/mlabonne_Meta-Llama-3-12B-Instruct-2_5bpw_exl2)**</center> | <center>4519 MB</center> | <center>6</center> |
|<center>**[3.0](https://huggingface.co/Zoyd/mlabonne_Meta-Llama-3-12B-Instruct-3_0bpw_exl2)**</center> | <center>5143 MB</center> | <center>6</center> |
|<center>**[3.5](https://huggingface.co/Zoyd/mlabonne_Meta-Llama-3-12B-Instruct-3_5bpw_exl2)**</center> | <center>5766 MB</center> | <center>6</center> |
|<center>**[3.75](https://huggingface.co/Zoyd/mlabonne_Meta-Llama-3-12B-Instruct-3_75bpw_exl2)**</center> | <center>6077 MB</center> | <center>6</center> |
|<center>**[4.0](https://huggingface.co/Zoyd/mlabonne_Meta-Llama-3-12B-Instruct-4_0bpw_exl2)**</center> | <center>6391 MB</center> | <center>6</center> |
|<center>**[4.25](https://huggingface.co/Zoyd/mlabonne_Meta-Llama-3-12B-Instruct-4_25bpw_exl2)**</center> | <center>6703 MB</center> | <center>6</center> |
|<center>**[5.0](https://huggingface.co/Zoyd/mlabonne_Meta-Llama-3-12B-Instruct-5_0bpw_exl2)**</center> | <center>7637 MB</center> | <center>6</center> |
|<center>**[6.0](https://huggingface.co/Zoyd/mlabonne_Meta-Llama-3-12B-Instruct-6_0bpw_exl2)**</center> | <center>8992 MB</center> | <center>8</center> |
|<center>**[6.5](https://huggingface.co/Zoyd/mlabonne_Meta-Llama-3-12B-Instruct-6_5bpw_exl2)**</center> | <center>9616 MB</center> | <center>8</center> |
|<center>**[8.0](https://huggingface.co/Zoyd/mlabonne_Meta-Llama-3-12B-Instruct-8_0bpw_exl2)**</center> | <center>11473 MB</center> | <center>8</center> |


# Meta-Llama-3-12B-Instruct

Meta-Llama-3-12B-Instruct is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct)
* [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct)
* [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct)
* [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct)
* [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct)

## 🏆 Evaluation

|                                        Model                                         |AGIEval|GPT4All|TruthfulQA|Bigbench|Average|
|--------------------------------------------------------------------------------------|------:|------:|---------:|-------:|------:|
|[Meta-Llama-3-12B-Instruct](https://huggingface.co/mlabonne/Meta-Llama-3-12B-Instruct)|   41.7|  67.71|     52.75|   40.58|  50.69|
|[Meta-Llama-3-12B](https://huggingface.co/mlabonne/Meta-Llama-3-12B)|  29.46|  68.01|     41.02|   35.57|  43.52|

## 🧩 Configuration

```yaml
slices:
  - sources:
    - model: NousResearch/Meta-Llama-3-8B-Instruct
      layer_range: [0,9]
  - sources:
    - model: NousResearch/Meta-Llama-3-8B-Instruct
      layer_range: [5,14]
  - sources:
    - model: NousResearch/Meta-Llama-3-8B-Instruct
      layer_range: [10,19]
  - sources:
    - model: NousResearch/Meta-Llama-3-8B-Instruct
      layer_range: [15,24]
  - sources:
    - model: NousResearch/Meta-Llama-3-8B-Instruct
      layer_range: [20,32]
merge_method: passthrough
dtype: bfloat16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "mlabonne/Meta-Llama-3-12B-Instruct"
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"])
```