chg: [user-manual] Improvements.

Author: cedricbonhomme

content/user-manual/ai/index.md

@@ -61,15 +61,20 @@ With the various vulnerability feeders of Vulnerability-Lookup (for the CVE Prog
 we’ve collected over a million JSON records. This allow us to generate datasets for training and building models.
 
 During our explorations, we realized that we can automatically update a BERT-based text classification model daily using a dataset of approximately 600k rows from Vulnerability-Lookup.
-With powerful GPUs, it’s a matter of hours. We are currenly using the RoBERTa base model.
+With powerful GPUs, it’s a matter of hours.
+
+Models are generated on our own GPUs and with our [various open source trainers](https://github.com/vulnerability-lookup/VulnTrain).
+
+Similar to the datasets, model updates are performed on a regular basis.
 
 
 ### Text classification
 
 #### vulnerability-severity-classification-roberta-base
 
-This model is a fine-tuned version of ``roberta-base`` on the dataset
+This model is a fine-tuned version of ``RoBERTa base`` on the dataset
 [CIRCL/vulnerability-scores](https://huggingface.co/datasets/CIRCL/vulnerability-scores).
+
 The time of generation with two GPUs NVIDIA L40S is approximately 6 hours.
 
 Try it with Python: