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Guilherme34
/
Firefly

Safetensors
llama
Merge
mergekit
lazymergekit
SicariusSicariiStuff/Impish_LLAMA_3B
Guilherme34/Lumina
ValiantLabs/Llama3.2-3B-Enigma
DavidAU/Llama-3.2-3B-Instruct-heretic-ablitered-uncensored
Model card Files
xet
Community
Firefly
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---
base_model:
- SicariusSicariiStuff/Impish_LLAMA_3B
- Guilherme34/Lumina
- ValiantLabs/Llama3.2-3B-Enigma
- DavidAU/Llama-3.2-3B-Instruct-heretic-ablitered-uncensored
tags:
- merge
- mergekit
- lazymergekit
- SicariusSicariiStuff/Impish_LLAMA_3B
- Guilherme34/Lumina
- ValiantLabs/Llama3.2-3B-Enigma
- DavidAU/Llama-3.2-3B-Instruct-heretic-ablitered-uncensored
---

# Firefly

Firefly is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [SicariusSicariiStuff/Impish_LLAMA_3B](https://huggingface.co/SicariusSicariiStuff/Impish_LLAMA_3B)
* [Guilherme34/Lumina](https://huggingface.co/Guilherme34/Lumina)
* [ValiantLabs/Llama3.2-3B-Enigma](https://huggingface.co/ValiantLabs/Llama3.2-3B-Enigma)
* [DavidAU/Llama-3.2-3B-Instruct-heretic-ablitered-uncensored](https://huggingface.co/DavidAU/Llama-3.2-3B-Instruct-heretic-ablitered-uncensored)

## 🧩 Configuration

```yaml
models:
  - model: SicariusSicariiStuff/Impish_LLAMA_3B
    parameters:
      weight: 1.0  

  - model: Guilherme34/Lumina
    parameters:
      weight: 0.75  

  - model: ValiantLabs/Llama3.2-3B-Enigma
    parameters:
      weight: 0.125  

  - model: DavidAU/Llama-3.2-3B-Instruct-heretic-ablitered-uncensored
    parameters:
      weight: 0.125  

merge_method: task_arithmetic
base_model: SicariusSicariiStuff/Impish_LLAMA_3B

dtype: bfloat16

parameters:
  normalize: true   
  int8_mask: true   
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Guilherme34/Firefly"
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"])
```