---
base_model: bobofrut/ladybird-base-7B-v8
license: apache-2.0
language:
  - en
pipeline_tag: text-generation
tags:
  - mistral
  - gguf
library_name: llama.cpp
model_creator: bobofrut
model_name: ladybird base 7B v8
model_type: mistral
prompt_template: |
  <|im_start|>system
  {system_message}<|im_end|>
  <|im_start|>user
  {prompt}<|im_end|>
  <|im_start|>assistant
quantized_by: mgonzs13
---

# ladybird-base-7B-v8

**Model creator:** [bobofrut](https://huggingface.co/bobofrut)<br>
**Original model**: [Mistroll-7B-v2.2](https://huggingface.co/bobofrut/ladybird-base-7B-v8)<br>
**GGUF quantization:** `llama.cpp` commit [b8c1476e44cc1f3a1811613f65251cf779067636](https://github.com/ggerganov/llama.cpp/tree/b8c1476e44cc1f3a1811613f65251cf779067636)<br>

## Description

Ladybird-base-7B-v8 is based on the Mistral architecture, which is known for its efficiency and effectiveness in handling complex language understanding and generation tasks. The model incorporates several innovative architecture choices to enhance its performance:

- **Grouped-Query Attention**: Optimizes attention mechanisms by grouping queries, reducing computational complexity while maintaining model quality.
- **Sliding-Window Attention**: Improves the model's ability to handle long-range dependencies by focusing on relevant segments of input, enhancing understanding and coherence.
- **Byte-fallback BPE Tokenizer**: Offers robust tokenization by combining the effectiveness of Byte-Pair Encoding (BPE) with a fallback mechanism for out-of-vocabulary bytes, ensuring comprehensive language coverage.

## Prompt Template

The prompt template is ChatML.

```
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
```