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---
base_model:
- Quazim0t0/Jekyl-8b-sce
- bunnycore/HyperLlama-3.1-8B
- Quazim0t0/GivingTree-8b-sce
- Quazim0t0/Chromatic-8b-sce
tags:
- merge
- mergekit
- lazymergekit
- Quazim0t0/Jekyl-8b-sce
- bunnycore/HyperLlama-3.1-8B
- Quazim0t0/GivingTree-8b-sce
- Quazim0t0/Chromatic-8b-sce
---
# Aura-8B-Linear
Aura-8B-Linear is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Quazim0t0/Jekyl-8b-sce](https://huggingface.co/Quazim0t0/Jekyl-8b-sce)
* [bunnycore/HyperLlama-3.1-8B](https://huggingface.co/bunnycore/HyperLlama-3.1-8B)
* [Quazim0t0/GivingTree-8b-sce](https://huggingface.co/Quazim0t0/GivingTree-8b-sce)
* [Quazim0t0/Chromatic-8b-sce](https://huggingface.co/Quazim0t0/Chromatic-8b-sce)
## 🧩 Configuration
```yaml
models:
- model: Quazim0t0/Jekyl-8b-sce
parameters:
weight: 1.0
- model: bunnycore/HyperLlama-3.1-8B
parameters:
weight: 1.5
- model: Quazim0t0/GivingTree-8b-sce
parameters:
weight: 1.0
- model: Quazim0t0/Chromatic-8b-sce
parameters:
weight: 1.0
merge_method: linear
normalize: false
int8_mask: true
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Quazim0t0/Aura-8B-Linear"
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"])
``` |