Pygmalion 2 7B GGUF

🚀 Pygmalion 2 7B - GGUF

This repository provides GGUF format model files for Pygmalion 2 7B, a text generation model. It details the model's characteristics, compatibility, and how to download and use it.

🚀 Quick Start

This repo offers GGUF format model files for PygmalionAI's Pygmalion 2 7B.

• Model creator: PygmalionAI
• Original model: Pygmalion 2 7B

✨ Features

• Text Generation: Capable of generating text based on given prompts.
• Custom Prompt Template: Uses a custom prompt template with <|system|>, <|user|> and <|model|> tokens for multi - role interactions.
• Multiple Quantization Methods: Offers various quantization methods for different use cases and hardware requirements.

📦 Installation

How to download GGUF files

Note for manual downloaders: You almost never want to clone the entire repo! Multiple different quantisation formats are provided, and most users only want to pick and download a single file.

The following clients/libraries will automatically download models for you, providing a list of available models to choose from:

• LM Studio
• LoLLMS Web UI
• Faraday.dev

In text-generation-webui

Under Download Model, you can enter the model repo: TheBloke/Pygmalion-2-7B-GGUF and below it, a specific filename to download, such as: pygmalion-2-7b.q4_K_M.gguf. Then click Download.

On the command line, including multiple files at once

I recommend using the huggingface-hub Python library:

pip3 install huggingface-hub>=0.17.1

Then you can download any individual model file to the current directory, at high speed, with a command like this:

huggingface-cli download TheBloke/Pygmalion-2-7B-GGUF pygmalion-2-7b.q4_K_M.gguf --local-dir . --local-dir-use-symlinks False

huggingface-cli download TheBloke/Pygmalion-2-7B-GGUF --local-dir . --local-dir-use-symlinks False --include='*Q4_K*gguf'

pip3 install hf_transfer

HUGGINGFACE_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download TheBloke/Pygmalion-2-7B-GGUF pygmalion-2-7b.q4_K_M.gguf --local-dir . --local-dir-use-symlinks False

💻 Usage Examples

Example llama.cpp command

Make sure you are using llama.cpp from commit d0cee0d36d5be95a0d9088b674dbb27354107221 or later.

./main -ngl 32 -m pygmalion-2-7b.q4_K_M.gguf --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "<|system|>Enter RP mode. Pretend to be {{char}} whose persona follows: {{persona}}. You shall reply to the user while staying in character, and generate long responses."

📚 Documentation

About GGUF

GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. GGUF offers numerous advantages over GGML, such as better tokenisation, and support for special tokens. It also supports metadata, and is designed to be extensible.

Here is an incomplete list of clients and libraries that are known to support GGUF:

• llama.cpp. The source project for GGUF. Offers a CLI and a server option.
• text-generation-webui, the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration.
• KoboldCpp, a fully featured web UI, with GPU accel across all platforms and GPU architectures. Especially good for story telling.
• LM Studio, an easy-to-use and powerful local GUI for Windows and macOS (Silicon), with GPU acceleration.
• LoLLMS Web UI, a great web UI with many interesting and unique features, including a full model library for easy model selection.
• Faraday.dev, an attractive and easy to use character-based chat GUI for Windows and macOS (both Silicon and Intel), with GPU acceleration.
• ctransformers, a Python library with GPU accel, LangChain support, and OpenAI-compatible AI server.
• llama-cpp-python, a Python library with GPU accel, LangChain support, and OpenAI-compatible API server.
• candle, a Rust ML framework with a focus on performance, including GPU support, and ease of use.

Prompt template: Custom

The model has been trained on prompts using three different roles, which are denoted by the following tokens: <|system|>, <|user|> and <|model|>.

The <|system|> prompt can be used to inject out-of-channel information behind the scenes, while the <|user|> prompt should be used to indicate user input. The <|model|> token should then be used to indicate that the model should generate a response. These tokens can happen multiple times and be chained up to form a conversation history.

The system prompt has been designed to allow the model to "enter" various modes and dictate the reply length. Here's an example:

<|system|>Enter RP mode. Pretend to be {{char}} whose persona follows:
{{persona}}

You shall reply to the user while staying in character, and generate long responses.

Compatibility

These quantised GGUFv2 files are compatible with llama.cpp from August 27th onwards, as of commit d0cee0d36d5be95a0d9088b674dbb27354107221

They are also compatible with many third party UIs and libraries - please see the list at the top of this README.

Explanation of quantisation methods

Provided files

Note: the above RAM figures assume no GPU offloading. If layers are offloaded to the GPU, this will reduce RAM usage and use VRAM instead.

Repositories available

• AWQ model(s) for GPU inference.
• GPTQ models for GPU inference, with multiple quantisation parameter options.
• 2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference
• PygmalionAI's original unquantised fp16 model in pytorch format, for GPU inference and for further conversions

📄 License

The model is licensed under llama2.

⚠️ Important Note

For manual downloaders, you almost never want to clone the entire repo as multiple different quantisation formats are provided, and most users only want to pick and download a single file.

💡 Usage Tip

When using the huggingface-cli to download files, you can use patterns to download multiple files at once. Also, installing hf_transfer can accelerate downloads on fast connections.