Teuken 7B Instruct Research V0.4 Q6 K GGUF

🚀 lukasfast/Teuken-7B-instruct-research-v0.4-Q6_K-GGUF

This model is converted to GGUF format, offering enhanced performance for text generation tasks.

🚀 Quick Start

This model was converted to GGUF format from openGPT-X/Teuken-7B-instruct-research-v0.4 using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

✨ Features

• Supported Languages: de, bg, cs, da, el, en, es, et, fi, fr, ga, hr, hu, it, lt, lv, mt, nl, pl, pt, ro, sl, sv, sk
• Metrics: accuracy, bleu
• Pipeline Tag: text-generation
• Library Name: transformers
• Base Model: openGPT-X/Teuken-7B-instruct-research-v0.4

📦 Installation

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

💻 Usage Examples

Basic Usage

CLI:

llama-cli --hf-repo lukasfast/Teuken-7B-instruct-research-v0.4-Q6_K-GGUF --hf-file teuken-7b-instruct-research-v0.4-q6_k.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo lukasfast/Teuken-7B-instruct-research-v0.4-Q6_K-GGUF --hf-file teuken-7b-instruct-research-v0.4-q6_k.gguf -c 2048

Advanced Usage

You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

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

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo lukasfast/Teuken-7B-instruct-research-v0.4-Q6_K-GGUF --hf-file teuken-7b-instruct-research-v0.4-q6_k.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo lukasfast/Teuken-7B-instruct-research-v0.4-Q6_K-GGUF --hf-file teuken-7b-instruct-research-v0.4-q6_k.gguf -c 2048

📄 License

The license for this model is other.