---
base_model:
- crestf411/L3-8B-sunfall-v0.4-stheno-v3.2
- Hastagaras/Jamet-8B-L3-MK.V-Blackroot
- Hastagaras/Jamet-8B-L3-MK.V-Blackroot
- TheDrummer/Llama-3SOME-8B-v2
tags:
- merge
- mergekit
- lazymergekit
- crestf411/L3-8B-sunfall-v0.4-stheno-v3.2
- Hastagaras/Jamet-8B-L3-MK.V-Blackroot
- TheDrummer/Llama-3SOME-8B-v2
---

# L3-Blackened-Sunfall-15B

L3-Blackened-Sunfall-15B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [crestf411/L3-8B-sunfall-v0.4-stheno-v3.2](https://huggingface.co/crestf411/L3-8B-sunfall-v0.4-stheno-v3.2)
* [Hastagaras/Jamet-8B-L3-MK.V-Blackroot](https://huggingface.co/Hastagaras/Jamet-8B-L3-MK.V-Blackroot)
* [Hastagaras/Jamet-8B-L3-MK.V-Blackroot](https://huggingface.co/Hastagaras/Jamet-8B-L3-MK.V-Blackroot)
* [TheDrummer/Llama-3SOME-8B-v2](https://huggingface.co/TheDrummer/Llama-3SOME-8B-v2)

## 🧩 Configuration

```yaml
dtype: bfloat16
merge_method: passthrough
slices:
- sources:
  - layer_range: [0, 20]
    model: crestf411/L3-8B-sunfall-v0.4-stheno-v3.2
- sources:
  - layer_range: [6, 24]
    model: Hastagaras/Jamet-8B-L3-MK.V-Blackroot
    parameters:
      scale:
      - filter: o_proj
        value: 0.0
      - filter: down_proj
        value: 0.0
      - value: 1.0
- sources:
  - layer_range: [8, 26]
    model: Hastagaras/Jamet-8B-L3-MK.V-Blackroot
    parameters:
      scale:
      - filter: o_proj
        value: 0.0
      - filter: down_proj
        value: 0.0
      - value: 1.0
- sources:
  - layer_range: [24, 32]
    model: TheDrummer/Llama-3SOME-8B-v2
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "kromeurus/L3-Blackened-Sunfall-15B"
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"])
```