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---
base_model: unsloth/gemma-2-9b-bnb-4bit
language:
- pt
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- gemma2
- gguf
---
# Boto 9B - GGUF
- Criador do Modelo: [Luciano Santa Brígida](https://lucianosb.com.br/)
- Modelo Original: [Boto-9B](https://huggingface.co/lucianosb/boto-9B)
Boto-9B é um modelo de linguagem de 9 bilhões de parâmetros, otimizado a partir do Gemma2-9B.
Confira os [presets](https://huggingface.co/lucianosb/boto-7B-GGUF/tree/main/presets) para usar com [LM Studio](https://lmstudio.ai/).
## Arquivos Incluídos
| Nome | Método Quant | Bits | Tamanho | Desc |
| ---- | ---- | ---- | ---- | ----- |
| [boto9b.Q2_K.gguf](https://huggingface.co/lucianosb/boto-9B-GGUF/blob/main/boto9b.Q2_K.gguf) | q2_K | 2 | 3.81 GB | Quantização em 2-bit. Significativa perda de qualidade. Não-recomendado. |
| [boto9b.Q3_K_M.gguf](https://huggingface.co/lucianosb/boto-9B-GGUF/blob/main/boto9b.Q3_K_M.gguf) | q3_K_M| 3 | 4.76 GB | Quantização em 3-bit. |
| [boto9b.Q3_K_S.gguf](https://huggingface.co/lucianosb/boto-9B-GGUF/blob/main/boto9b.Q3_K_S.gguf) | q3_K_S | 3 | 4.34 GB | Quantização em 3-bit. |
| [boto9b.Q4_0.gguf](https://huggingface.co/lucianosb/boto-9B-GGUF/blob/main/boto9b.Q4_0.gguf) | q4_0 | 4 | 5.44 GB | Quantização em 4-bit. Prefira usar o Q3_K_M|
| [boto9b.Q4_K_S.gguf](https://huggingface.co/lucianosb/boto-9B-GGUF/blob/main/boto9b.Q4_K_S.gguf) | q4_K_S | 4 | 5.48 GB | Quantização em 4-bit. |
| [boto9b.Q3_K_L.gguf](https://huggingface.co/lucianosb/boto-9B-GGUF/blob/main/boto9b.Q3_K_L.gguf) | q3_K_L | 3 | 5.13 GB | Quantização em 3-bit com menor perda de qualidade. |
| [boto9b.Q4_K_M.gguf](https://huggingface.co/lucianosb/boto-9B-GGUF/blob/main/boto9b.Q4_K_M.gguf) | q4_K_M | 4 | 5.76 GB | Quantização em 4-bit. |
| [boto9b.Q4_1.gguf](https://huggingface.co/lucianosb/boto-9B-GGUF/blob/main/boto9b.Q4_1.gguf) | q4_1 | 4 | 5.96 GB | Quantização em 4-bit. Acurácia maior que q4_0 mas não tão boa quanto q5_0. Inferência mais rápida que os modelos q5. |
| [boto9b.Q5_0.gguf](https://huggingface.co/lucianosb/boto-9B-GGUF/blob/main/boto9b.Q5_0.gguf) | q5_0 | 5 | 6.48 GB | Quantização em 5-bit. Melhor acurácia, maior uso de recursos, inferência mais lenta. |
| [boto9b.Q5_1.gguf](https://huggingface.co/lucianosb/boto-9B-GGUF/blob/main/boto9b.Q5_1.gguf) | q5_1 | 5 | 7 GB | Quantização em 5-bit. Ainda Melhor acurácia, maior uso de recursos, inferência mais lenta. |
| [boto9b.Q5_K_M.gguf](https://huggingface.co/lucianosb/boto-9B-GGUF/blob/main/boto9b.Q5_K_M.gguf) | q5_K_M | 5 | 6.65 GB | Quantização em 5-bit. Melhor performance. Recomendado. |
| [boto9b.Q5_K_S.gguf](https://huggingface.co/lucianosb/boto-9B-GGUF/blob/main/boto9b.Q5_K_S.gguf) | q5_K_S | 5 | 6.48 GB | Quantização em 5-bit. |
| [boto9b.Q6_K.gguf](https://huggingface.co/lucianosb/boto-9B-GGUF/blob/main/boto9b.Q6_K.gguf) | q6_K | 6 | 7.59 GB | Quantização em 6-bit. |
| [boto9b.Q8_0.gguf](https://huggingface.co/lucianosb/boto-9B-GGUF/blob/main/boto9b.Q8_0.gguf) | q8_0 | 8 | 9.83 GB | Quantização em 8-bit. Quase indistinguível do float16. Usa muitos recursos e é mais lento. |
**Observação**: os valores de RAM acima não pressupõem descarregamento de GPU. Se as camadas forem descarregadas para a GPU, isso reduzirá o uso de RAM e usará VRAM.
## Template
````
### Instrução:
{prompt}
### Resposta:
````
# Uploaded model
- **Developed by:** lucianosb
- **License:** apache-2.0
- **Finetuned from model :** unsloth/gemma-2-9b-bnb-4bit
This gemma2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

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{
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}