---
base_model: unsloth/Meta-Llama-3.1-8B-bnb-4bit
library_name: peft
pipeline_tag: text-generation
tags:
- base_model:adapter:unsloth/Meta-Llama-3.1-8B-bnb-4bit
- lora
- sft
- transformers
- trl
- unsloth
---

# Model Card


## Model Description

A French grammar correction model designed primarily for learners of French as a second language (FSL/FLE). It corrects grammar, spelling, syntax, punctuation, and stylistic issues while preserving the original meaning and tone as much as possible.

The model is especially effective for:

- French learners and students
- Academic and professional writing
- Language practice and self-correction
- Improving fluency and sentence naturalness

It can also perform high-quality translation from English to French, making it useful both as a grammar corrector and as a lightweight bilingual writing assistant.

Optimized for local inference with LM Studio and compatible with GGUF quantizations for efficient CPU or GPU deployment.


- **Developed by:** Adel Jebali, Concordia University
- **Funded by:** SSHRC
- **Language(s) (NLP):** French
- **License:** Apache 2.0
- **Finetuned:** from Llama 3.1-8B

## Uses

Correct you French written texts! It is not a chat model.


## Bias, Risks, and Limitations

This AI LLM is not 100% bullet-proof. Errors are still possible.


## How to use

Works best with [LM Studio](https://lmstudio.ai) and is available in three quantization formats:

* **4-bit — Q4_K_M — 4.92 GB**
  Best choice for low-memory systems and entry-level hardware. Recommended for Macs with only 8 GB of unified memory or older GPUs. Offers the fastest loading times and lowest VRAM usage, with a small trade-off in output quality and coherence.

* **6-bit — Q6_K — 6.6 GB**
  Excellent balance between quality, speed, and memory consumption. A strong default option for most users with 12–16 GB of RAM or mid-range GPUs. In many cases, it delivers quality close to 8-bit while remaining significantly lighter.

* **8-bit — Q8_0 — 8.54 GB**
  Highest quality and most faithful outputs among the available quantizations. Recommended if your hardware can handle it, especially with a dedicated GPU or Apple Silicon Mac with sufficient unified memory. Produces more stable generations, better grammatical consistency, and fewer hallucinations.

## Recommendations

* **8 GB Macs:** use **Q4_K_M**
* **16 GB systems:** use **Q6_K** for the best balance
* **24 GB+ RAM or modern GPU:** use **Q8_0** for maximum quality

For optimal performance in [LM Studio](https://lmstudio.ai):

* Enable **GPU offloading** when available
* Increase the **context length** only if needed, since larger contexts consume more memory
* On Apple Silicon Macs, Metal acceleration significantly improves inference speed
* Temperature 0 (or 0.1)
* Min p 0
* Top k 0
* Top p 1

If your priority is:

* **Maximum speed / lowest memory usage → Q4_K_M**
* **Best balance → Q6_K**
* **Best overall quality → Q8_0**


# Paper
A. Jebali, "Developing a Grammatical Error Correction System for French Second Language Written Texts," 2025 5th International Conference on Electrical, Computer and Energy Technologies (ICECET), Paris, France, 2025, pp. 1-6, doi: 10.1109/ICECET63943.2025.11472110.