---
tags:
- merge
- mergekit
- lazymergekit
- Hypersniper/The_Philosopher_Zephyr_7B
- sayhan/OpenHermes-2.5-Strix-Philosophy-Mistral-7B-LoRA
- teknium/Mistral-Trismegistus-7B
base_model:
- Hypersniper/The_Philosopher_Zephyr_7B
- sayhan/OpenHermes-2.5-Strix-Philosophy-Mistral-7B-LoRA
- teknium/Mistral-Trismegistus-7B
---

# Trascendental-Bot-7B


![image/png](https://cdn-uploads.huggingface.co/production/uploads/64d71ab4089bc502ceb44d29/vHD7qJpFPXEc6CcE36vwQ.png)


![image/png](https://cdn-uploads.huggingface.co/production/uploads/64d71ab4089bc502ceb44d29/7dce-wRl3enecV7Y3GBfe.png)

Trascendental-Bot-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Hypersniper/The_Philosopher_Zephyr_7B](https://huggingface.co/Hypersniper/The_Philosopher_Zephyr_7B)
* [sayhan/OpenHermes-2.5-Strix-Philosophy-Mistral-7B-LoRA](https://huggingface.co/sayhan/OpenHermes-2.5-Strix-Philosophy-Mistral-7B-LoRA)
* [teknium/Mistral-Trismegistus-7B](https://huggingface.co/teknium/Mistral-Trismegistus-7B)

## 🧩 Configuration

```yaml
models:
  - model: teknium/Mistral-Trismegistus-7B
    # no parameters necessary for base model
  - model: Hypersniper/The_Philosopher_Zephyr_7B
    parameters:
      density: 0.55
      weight: 0.3
  - model: sayhan/OpenHermes-2.5-Strix-Philosophy-Mistral-7B-LoRA
    parameters:
      density: 0.55
      weight: 0.3
  - model: teknium/Mistral-Trismegistus-7B
    parameters:
      density: 0.4
      weight: 0.66
merge_method: dare_ties
base_model: teknium/Mistral-Trismegistus-7B
parameters:
  int8_mask: true
dtype: bfloat16
random_seed: 0

```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Kukedlc/Trascendental-Bot-7B"
messages = [
    {"role": "system", "content": "You are an expert assistant in mysticism and philosophy."},
    {"role": "user", "content": "Create an innovative and disruptive theory that explains human consciousness. Give me an extensive and detailed answer."}
]

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=1024, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```