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---
tags:
- merge
- mergekit
- lazymergekit
language:
- en
base_model:
- Marcjoni/SuperNovaSynth-12B
- yamatazen/LorablatedStock-12B
---
<img src="./HyperNova.png" alt="Model Image"/>
# HyperNovaSynth-12B
<b><i>From the void where giants fall, a deeper silence erupts. Darker, heavier, stranger.
<br> What follows is not light but gravity itself made song.
<br> This is no ordinary flare, but the whisper of something vast unraveling.</i></b>
## 🔧 Recommended Sampling Settings:</b>
```yaml
Temperature: 0.75 to 1.25
Min P: 0.035
Context Length: Stable at 12k tokens, with possible support for extended contexts
```
## 💬 Prompt Format
Supports ChatML style messages. Example:
```yaml
<|im_start|>user
Your question here.
<|im_end|>
<|im_start|>assistant
```
HyperNovaSynth-12B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
## 🧩 Configuration
```yaml
merge_method: slerp
base_model: Marcjoni/SuperNovaSynth-12B
models:
- model: yamatazen/LorablatedStock-12B
parameters:
t:
- filter: "mlp"
value: 0.75
- filter: "attn"
value: 0.35
- value: 0.55
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Marcjoni/HyperNovaSynth-12B"
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=1, top_k=0, top_p=1)
print(outputs[0]["generated_text"])
``` |