nvhf's picture
Upload README.md with huggingface_hub
2963c25 verified
---
base_model: grammarly/coedit-large
datasets:
- facebook/asset
- wi_locness
- GEM/wiki_auto_asset_turk
- discofuse
- zaemyung/IteraTeR_plus
- jfleg
- grammarly/coedit
language:
- en
license: cc-by-nc-4.0
metrics:
- sari
- bleu
- accuracy
tags:
- llama-cpp
- gguf-my-repo
widget:
- text: 'Fix the grammar: When I grow up, I start to understand what he said is quite
right.'
example_title: Fluency
- text: 'Make this text coherent: Their flight is weak. They run quickly through the
tree canopy.'
example_title: Coherence
- text: 'Rewrite to make this easier to understand: A storm surge is what forecasters
consider a hurricane''s most treacherous aspect.'
example_title: Simplification
- text: 'Paraphrase this: Do you know where I was born?'
example_title: Paraphrase
- text: 'Write this more formally: omg i love that song im listening to it right now'
example_title: Formalize
- text: 'Write in a more neutral way: The authors'' exposé on nutrition studies.'
example_title: Neutralize
---
# nvhf/coedit-large-Q6_K-GGUF
This model was converted to GGUF format from [`grammarly/coedit-large`](https://huggingface.co/grammarly/coedit-large) 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/grammarly/coedit-large) 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 nvhf/coedit-large-Q6_K-GGUF --hf-file coedit-large-q6_k.gguf -p "The meaning to life and the universe is"
```
### Server:
```bash
llama-server --hf-repo nvhf/coedit-large-Q6_K-GGUF --hf-file coedit-large-q6_k.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 nvhf/coedit-large-Q6_K-GGUF --hf-file coedit-large-q6_k.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo nvhf/coedit-large-Q6_K-GGUF --hf-file coedit-large-q6_k.gguf -c 2048
```