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---
license: other
tags:
- merge
- mergekit
- lazymergekit
base_model:
- nbeerbower/llama-3-stella-8B
- Hastagaras/llama-3-8b-okay
- nbeerbower/llama-3-gutenberg-8B
- openchat/openchat-3.6-8b-20240522
- Kukedlc/NeuralLLaMa-3-8b-DT-v0.1
- cstr/llama3-8b-spaetzle-v20
- mlabonne/ChimeraLlama-3-8B-v3
- flammenai/Mahou-1.1-llama3-8B
- KingNish/KingNish-Llama3-8b
---
# Daredevil-8B
**tl;dr: It looks like a successful merge**
Daredevil-8B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [nbeerbower/llama-3-stella-8B](https://huggingface.co/nbeerbower/llama-3-stella-8B)
* [Hastagaras/llama-3-8b-okay](https://huggingface.co/Hastagaras/llama-3-8b-okay)
* [nbeerbower/llama-3-gutenberg-8B](https://huggingface.co/nbeerbower/llama-3-gutenberg-8B)
* [openchat/openchat-3.6-8b-20240522](https://huggingface.co/openchat/openchat-3.6-8b-20240522)
* [Kukedlc/NeuralLLaMa-3-8b-DT-v0.1](https://huggingface.co/Kukedlc/NeuralLLaMa-3-8b-DT-v0.1)
* [cstr/llama3-8b-spaetzle-v20](https://huggingface.co/cstr/llama3-8b-spaetzle-v20)
* [mlabonne/ChimeraLlama-3-8B-v3](https://huggingface.co/mlabonne/ChimeraLlama-3-8B-v3)
* [flammenai/Mahou-1.1-llama3-8B](https://huggingface.co/flammenai/Mahou-1.1-llama3-8B)
* [KingNish/KingNish-Llama3-8b](https://huggingface.co/KingNish/KingNish-Llama3-8b)
## π Applications
It is a highly functional censored model. You might want to add `<end_of_turn>` as an additional stop string.
## β‘ Quantization
* **GGUF**: https://huggingface.co/mlabonne/Daredevil-8B-GGUF
## π Evaluation
| Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench |
| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------: | --------: | --------: | ---------: | --------: |
| [**mlabonne/Daredevil-8B**](https://huggingface.co/mlabonne/Daredevil-8B) [π](https://gist.github.com/mlabonne/080f9c5f153ea57a7ab7d932cf896f21) | **55.87** | **44.13** | **73.52** | **59.05** | **46.77** |
| [mlabonne/ChimeraLlama-3-8B](https://huggingface.co/mlabonne/Chimera-8B) [π](https://gist.github.com/mlabonne/28d31153628dccf781b74f8071c7c7e4) | 51.58 | 39.12 | 71.81 | 52.4 | 42.98 |
| [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) [π](https://gist.github.com/mlabonne/8329284d86035e6019edb11eb0933628) | 51.34 | 41.22 | 69.86 | 51.65 | 42.64 |
| [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) [π](https://gist.github.com/mlabonne/616b6245137a9cfc4ea80e4c6e55d847) | 45.42 | 31.1 | 69.95 | 43.91 | 36.7 |
## π³ Model family tree
![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/LplqNg6iXHm_JXfX02Aj1.png)
## 𧩠Configuration
```yaml
models:
- model: NousResearch/Meta-Llama-3-8B
# No parameters necessary for base model
- model: nbeerbower/llama-3-stella-8B
parameters:
density: 0.6
weight: 0.16
- model: Hastagaras/llama-3-8b-okay
parameters:
density: 0.56
weight: 0.1
- model: nbeerbower/llama-3-gutenberg-8B
parameters:
density: 0.6
weight: 0.18
- model: openchat/openchat-3.6-8b-20240522
parameters:
density: 0.56
weight: 0.12
- model: Kukedlc/NeuralLLaMa-3-8b-DT-v0.1
parameters:
density: 0.58
weight: 0.18
- model: cstr/llama3-8b-spaetzle-v20
parameters:
density: 0.56
weight: 0.08
- model: mlabonne/ChimeraLlama-3-8B-v3
parameters:
density: 0.56
weight: 0.08
- model: flammenai/Mahou-1.1-llama3-8B
parameters:
density: 0.55
weight: 0.05
- model: KingNish/KingNish-Llama3-8b
parameters:
density: 0.55
weight: 0.05
merge_method: dare_ties
base_model: NousResearch/Meta-Llama-3-8B
dtype: bfloat16
```
## π» Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "mlabonne/Daredevil-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"])
``` |