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Model: adeljebali/llama3.1-gec-strict
Source: Original Platform

README.md

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+---
+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.