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README.md
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---
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base_model: grammarly/coedit-large
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datasets:
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- facebook/asset
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- wi_locness
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- GEM/wiki_auto_asset_turk
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- discofuse
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- zaemyung/IteraTeR_plus
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- jfleg
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- grammarly/coedit
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language:
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- en
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license: cc-by-nc-4.0
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metrics:
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- sari
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- bleu
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- accuracy
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tags:
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- llama-cpp
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- gguf-my-repo
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widget:
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- text: 'Fix the grammar: When I grow up, I start to understand what he said is quite
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right.'
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example_title: Fluency
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- text: 'Make this text coherent: Their flight is weak. They run quickly through the
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tree canopy.'
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example_title: Coherence
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- text: 'Rewrite to make this easier to understand: A storm surge is what forecasters
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consider a hurricane''s most treacherous aspect.'
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example_title: Simplification
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- text: 'Paraphrase this: Do you know where I was born?'
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example_title: Paraphrase
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- text: 'Write this more formally: omg i love that song im listening to it right now'
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example_title: Formalize
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- text: 'Write in a more neutral way: The authors'' exposé on nutrition studies.'
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example_title: Neutralize
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---
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# nvhf/coedit-large-Q6_K-GGUF
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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.
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Refer to the [original model card](https://huggingface.co/grammarly/coedit-large) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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```bash
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brew install llama.cpp
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```
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Invoke the llama.cpp server or the CLI.
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### CLI:
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```bash
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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"
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```
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### Server:
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```bash
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llama-server --hf-repo nvhf/coedit-large-Q6_K-GGUF --hf-file coedit-large-q6_k.gguf -c 2048
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```
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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.
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Step 1: Clone llama.cpp from GitHub.
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```
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git clone https://github.com/ggerganov/llama.cpp
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```
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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).
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```
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cd llama.cpp && LLAMA_CURL=1 make
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```
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Step 3: Run inference through the main binary.
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```
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./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"
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```
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or
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```
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./llama-server --hf-repo nvhf/coedit-large-Q6_K-GGUF --hf-file coedit-large-q6_k.gguf -c 2048
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```
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