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---
base_model:
- NousResearch/Hermes-2-Theta-Llama-3-8B
- mlabonne/NeuralDaredevil-8B-abliterated
- cognitivecomputations/dolphin-2.9.3-llama-3-8b
tags:
- merge
- mergekit
- lazymergekit
- NousResearch/Hermes-2-Theta-Llama-3-8B
- mlabonne/NeuralDaredevil-8B-abliterated
- cognitivecomputations/dolphin-2.9.3-llama-3-8b
---
# NeuralPipe-7B-slerp
NeuralPipe-7B-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [NousResearch/Hermes-2-Theta-Llama-3-8B](https://huggingface.co./NousResearch/Hermes-2-Theta-Llama-3-8B)
* [mlabonne/NeuralDaredevil-8B-abliterated](https://huggingface.co./mlabonne/NeuralDaredevil-8B-abliterated)
* [cognitivecomputations/dolphin-2.9.3-llama-3-8b](https://huggingface.co./cognitivecomputations/dolphin-2.9.3-llama-3-8b)
## 🧩 Configuration
```yaml
models:
- model: meta-llama/Meta-Llama-3-8B-Instruct
- model: NousResearch/Hermes-2-Theta-Llama-3-8B
parameters:
density: 0.53
weight: 0.4
- model: mlabonne/NeuralDaredevil-8B-abliterated
parameters:
density: 0.56
weight: 0.4
- model: cognitivecomputations/dolphin-2.9.3-llama-3-8b
parameters:
density: 0.53
weight: 0.3
merge_method: dare_ties
base_model: meta-llama/Meta-Llama-3-8B-Instruct
parameters:
int8_mask: true
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Trisert/NeuralPipe-7B-slerp"
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"])
``` |