Update README.md

README.md

@@ -8,18 +8,44 @@ tags:
 - mergekit
 - lazymergekit
 - mistral
+- hermes
 ---
 # SUONG-4 (7B Parameters)
 
-This is a merge of pre-trained language models created using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing), combining the strengths of NeuralHermes and OpenHermes models.
+This is a merge of pre-trained language models created using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing), combining the strengths of NeuralHermes and OpenHermes architectures through an optimized progressive fusion approach.
 
-[... reste de la présentation personnelle ...]
+## About Me
+I'm David Soeiro-Vuong, a third-year Computer Science student working as an apprentice at TW3 Partners, a company specialized in Generative AI. Passionate about artificial intelligence and language models optimization, I focus on creating efficient model merges that balance performance and capabilities.
+
+🔗 [Connect with me on LinkedIn](https://www.linkedin.com/in/david-soeiro-vuong-a28b582ba/)
 
 ## Merge Details
 ### Merge Method
-This model uses SLERP (Spherical Linear Interpolation) with a progressive fusion approach:
+This model uses SLERP (Spherical Linear Interpolation) with a carefully tuned progressive fusion approach:
 - Progressive attention layer fusion (0 to 1)
 - Inverse MLP layer transition (1 to 0)
 - Global fusion ratio of 0.45
+- bfloat16 format for efficient memory usage
+
+### Models Merged
+* [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B)
+* [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B)
 
-[... reste de la model card avec la configuration et le code d'utilisation ...]
+### Configuration
+```yaml
+slices:
+  - sources:
+      - model: mlabonne/NeuralHermes-2.5-Mistral-7B
+        layer_range: [0, 32]
+      - model: teknium/OpenHermes-2.5-Mistral-7B
+        layer_range: [0, 32]
+merge_method: slerp
+base_model: mlabonne/NeuralHermes-2.5-Mistral-7B
+parameters:
+  t:
+    - filter: self_attn
+      value: [0, 0.3, 0.6, 0.9, 1]  # Progressive fusion des couches d'attention
+    - filter: mlp
+      value: [1, 0.7, 0.4, 0.1, 0]  # Transition inverse pour les MLP
+    - value: 0.45  # Ratio de fusion global
+dtype: bfloat16