Update README.md

README.md

@@ -8,16 +8,39 @@ base_model:
 - meta-llama/Llama-3.2-3B-Instruct
 pipeline_tag: text2text-generation
 library_name: transformers
+tags:
+- llama
+- education
+- text-generation
 ---
-# Llama-3.2-3B-appreciation-full a merged version of Llama-3.2-3B-appreciation
-Alpha merged version of [eltorio/Llama-3.2-3B-appreciation](https://huggingface.co/eltorio/Llama-3.2-3B-appreciation)  
-See original model for documentation…  
+# Llama-3.2-3B-appreciation-full
 
-### Sample notebook:  
-You need to set the `HF_TOKEN` environment variable to a Hugging Face token with access to the `meta/llama 3.2` modell family.
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/#fileId=https://huggingface.co/eltorio/Llama-3.2-3B-appreciation-full/blob/main/llama-3-2-3b-appreciation-full-inference-test.ipynb)
+## Model Overview
+Merged version of [eltorio/Llama-3.2-3B-appreciation](https://huggingface.co/eltorio/Llama-3.2-3B-appreciation), optimized for generating student evaluations in French.
 
-### Sample inference code:  
+## Key Features
+- Generates personalized student evaluations in French
+- Trained on teacher-written reports
+- Optimized for concise feedback (40 words max)
+- Focuses on constructive assessment
+
+## Use Cases
+- Generating personalized student evaluations
+- Assisting teachers with report writing
+- Analyzing student performance patterns
+
+## Performance & Limitations
+- Optimized for short texts (max 40 words)
+- Best results for history-geography evaluations
+- May exhibit biases from training data
+
+## Technical Details
+Base model: meta-llama/Llama-3.2-3B-Instruct
+Training method: LoRA with PEFT
+Merged using: [Kaggle notebook](https://colab.research.google.com/#https://huggingface.co/eltorio/Llama-3.2-3B-appreciation-full/blob/main/llama-3-2-3b-appreciation-merge.ipynb)  
+Running it on Colab needs a trivial modification to the Hugging face login !
+
+## Quick Start
 ```python
 # -*- coding: utf-8 -*-
 """
@@ -70,4 +93,18 @@ outputs = model.generate(input_ids = inputs,
 decoded_sequences = tokenizer.batch_decode(outputs[:, inputs.shape[1]:],skip_special_tokens=True)[0]
 
 print(decoded_sequences)
-```
+```
+## Example Outputs
+- "Le bilan du trimestre est plutôt positif. X travaille dur, son niveau est correct et son attitude très positive. Il est donc tout à fait possible de réussir cette année. Attention toutefois aux bavardages et aux distractions en classe."
+- "Elève sérieux tout au long de l'année. X n'aurait pas pu avoir plus de succès s'il s’était plus impliqué en classe. Attention aux bavardages!"
+- "C'est un très bon trimestre. Le travail reste très sérieux et la participation tout à fait régulière. Bravo!"
+
+## Reproduction
+Model merged on Kaggle. Available notebooks:
+- Merging notebook [![Merging notebook](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/#https://huggingface.co/eltorio/Llama-3.2-3B-appreciation-full/blob/main/llama-3-2-3b-appreciation-merge.ipynb)
+- Inference notebook [![Inference notebook](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/#fileId=https://huggingface.co/eltorio/Llama-3.2-3B-appreciation-full/blob/main/llama-3-2-3b-appreciation-full-inference-test.ipynb)
+
+## License
+This model is licensed under AGPL-3.0
+
+## Citation