---
pipeline_tag: text-generation
inference: false
library_name: llama.cpp
license: cc-by-nc-sa-4.0
license_name: creative-commons
license_link: https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en
language:
    - en
tags:
    - text-generation
    - artificial-intelligence
    - not-for-all-audiences
---

## Valerie v0.1 Model Card

## Overview

Valerie v0.1 is a custom language model created using `llama.cpp` (commit: 532c173) with a context length of 256 tokens, embedding length of 256, 8 heads, and 16 layers. This model was pretrained on a dataset consisting of [female V's](https://cyberpunk.fandom.com/wiki/V_(character)) dialog from [Cyberpunk 2077](https://cyberpunk.fandom.com/wiki/Cyberpunk_Wiki), extracted using the [Voice Over Subtitle Map](https://www.nexusmods.com/cyberpunk2077/mods/2045) mod.

The `ggml-valerie-v0.1-256x32-f32-LATEST.gguf` release represents a single pass through all 51443 samples, completing one iteration over the entire dataset, and took approximately 3 hours for training.

## Model Information

| Model name              | Adam iteration | Model filename                           | Vocabulary size |
| ----------------------- | -------------- | ---------------------------------------- | --------------- |
| Valerie v0.1 Checkpoint | 950            | chk-valerie-v0.1-256x32-950.gguf         | 32,000          |
| Valerie v0.1 Model      | 1700           | ggml-valerie-v0.1-256x32-f32-LATEST.gguf | 32,000          |

### Files and versions

-   ggml-vocab-mistral.gguf: Extracted Mistral 7B model vocabulary
-   ggml-valerie-v0.1-256x32-f32-950.gguf: The pretrained model checkpoint version 950.
-   ggml-valerie-v0.1-256x32-f32-LATEST.gguf: The latest pretrained model checkpoint.

## Settings

-   Vocabulary size: 32,000
-   Context length: 256 tokens
-   Embedding length: 256
-   Heads: 8
-   Layers: 16
-   Batch size: 32
-   Seed: 1
-   Saved checkpoint every 50 iterations

## Usage

To use Valerie v0.1, follow these steps:

1. Clone the `llama.cpp` library

```sh
git clone https://github.com/ggerganov/llama.cpp
```

Reference the `llama.cpp` [README.md](https://github.com/ggerganov/llama.cpp/blob/master/README.md) for more information about building. You can build using raw CPU or even OpenBLAS. CUDA, ROCm, Vulkan, and other backends are also available.

Arch Linux Example:

```sh
# CPU build using BLAS backend on Arch Linux
sudo pacman -S openblas openblas64
make LLAMA_OPENBLAS=1
```

2. Download the latest model.

```sh
wget https://huggingface.co/teleprint-me/cyberpunk-valerie-v0.1/resolve/main/ggml-valerie-v0.1-256x32-f32-LATEST.gguf?download=true -O 
ggml-valerie-v0.1-256x32-f32-LATEST.gguf
```

This will download the latest available base model.

3. Perform inference with the latest model checkpoint using the provided command:

```sh
./main -m models/valerie/v0.1/ggml-valerie-v0.1-256x32-f32-LATEST.gguf --color -e -s 1 -c 4096
```

## Citations

When using Valerie v0.1 in your research, please remember to cite the following:

-   Aberrio. (2024). Valerie v0.1: A custom language model for female V's dialog from Cyberpunk 2077. <https://huggingface.co/teleprint-me/cyberpunk-valerie-v0.1>
-   GGML team. (2023). `llama.cpp` version `532c173`. Georgi Gerganov Machine Learning Library. <https://github.com/ggerganov/llama.cpp>
-   MistralAI (2023). Extracted sentencepiece model vocabulary: <https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2>
-   julieisdead (2021). Voice Over Subtitle Map: Two files that contain the IDs for, Voice Over files the other Subtitles. <https://www.nexusmods.com/cyberpunk2077/mods/2045>

### Contributors

Austin Berrio (teleprint-me) - Created and trained Valerie v0.1 using `llama.cpp` and the referenced dataset.

### Community

Join the community of fellow language model enthusiasts and researchers by sharing your knowledge, asking questions, and collaborating on projects related to creating custom models using `llama.cpp`.

### License

Valerie v0.1 is released under the CC-BY-NC-SA-3.0 license. You are free to use, modify, and redistribute this model for non-commercial purposes, but you must provide attribution to the original authors and release any derived works under the same license.