Model: adeljebali/llama3.1-gec-strict Source: Original Platform
base_model, library_name, pipeline_tag, tags
| base_model | library_name | pipeline_tag | tags | ||||||
|---|---|---|---|---|---|---|---|---|---|
| unsloth/Meta-Llama-3.1-8B-bnb-4bit | peft | text-generation |
|
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 and is available in three quantization formats:
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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.
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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:
- 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.