---
license: openrail
inference:
  parameters:
    num_beams: 3
    num_beam_groups: 3
    num_return_sequences: 1
    repetition_penalty: 3
    diversity_penalty: 3.01
    no_repeat_ngram_size: 2
    temperature: 0.8
    max_length: 64
widget:
- text: 'paraphraser: Learn to build generative AI applications with an expert AWS
    instructor with the 2-day Developing Generative AI Applications on AWS course.'
  example_title: AWS course
- text: 'paraphraser: In healthcare, Generative AI can help generate synthetic medical
    data to train machine learning models, develop new drug candidates, and design
    clinical trials.'
  example_title: Generative AI
- text: 'paraphraser: By leveraging prior model training through transfer learning,
    fine-tuning can reduce the amount of expensive computing power and labeled data
    needed to obtain large models tailored to niche use cases and business needs.'
  example_title: Fine Tuning
tags:
- llama-cpp
- gguf-my-repo
base_model: Ateeqq/Text-Rewriter-Paraphraser
---

# sizrox/Text-Rewriter-Paraphraser-Q8_0-GGUF
This model was converted to GGUF format from [`Ateeqq/Text-Rewriter-Paraphraser`](https://huggingface.co/Ateeqq/Text-Rewriter-Paraphraser) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/Ateeqq/Text-Rewriter-Paraphraser) for more details on the model.

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

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo sizrox/Text-Rewriter-Paraphraser-Q8_0-GGUF --hf-file text-rewriter-paraphraser-q8_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo sizrox/Text-Rewriter-Paraphraser-Q8_0-GGUF --hf-file text-rewriter-paraphraser-q8_0.gguf -c 2048
```

Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) 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 sizrox/Text-Rewriter-Paraphraser-Q8_0-GGUF --hf-file text-rewriter-paraphraser-q8_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo sizrox/Text-Rewriter-Paraphraser-Q8_0-GGUF --hf-file text-rewriter-paraphraser-q8_0.gguf -c 2048
```