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---
tags:
- merge
- mergekit
- lazymergekit
- bardsai/jaskier-7b-dpo-v3.3
- Kquant03/NeuralTrix-7B-dpo-laser
- CultriX/NeuralTrix-v4-bf16
- CultriX/NeuralTrix-V2
base_model:
- bardsai/jaskier-7b-dpo-v3.3
- Kquant03/NeuralTrix-7B-dpo-laser
- CultriX/NeuralTrix-v4-bf16
- CultriX/NeuralTrix-V2
---
# NeuralTrixlaser-bf16
NeuralTrixlaser-bf16 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [bardsai/jaskier-7b-dpo-v3.3](https://huggingface.co/bardsai/jaskier-7b-dpo-v3.3)
* [Kquant03/NeuralTrix-7B-dpo-laser](https://huggingface.co/Kquant03/NeuralTrix-7B-dpo-laser)
* [CultriX/NeuralTrix-v4-bf16](https://huggingface.co/CultriX/NeuralTrix-v4-bf16)
* [CultriX/NeuralTrix-V2](https://huggingface.co/CultriX/NeuralTrix-V2)
## 🧩 Configuration
```yaml
models:
- model: eren23/dpo-binarized-NeuralTrix-7B
# no parameters necessary for base model
- model: bardsai/jaskier-7b-dpo-v3.3
parameters:
density: 0.65
weight: 0.4
- model: Kquant03/NeuralTrix-7B-dpo-laser
parameters:
density: 0.6
weight: 0.35
- model: CultriX/NeuralTrix-v4-bf16
parameters:
density: 0.55
weight: 0.15
- model: CultriX/NeuralTrix-V2
parameters:
density: 0.55
weight: 0.15
merge_method: dare_ties
base_model: eren23/dpo-binarized-NeuralTrix-7B
parameters:
int8_mask: true
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "CultriX/"
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"])
``` |