Update README.md

README.md

@@ -9,59 +9,32 @@ tags:
 - mergekit
 ---
 
-# **ECE-TRIOMPHANT-2.1-YL-72B-SLERP-V1**
+# **rombodawg-Rombos-LLM-V2.5-Qwen-32b-Sakalt-Ultiima-32B-SLERP-V1**
 
-This model has been produced by:
-- **ROBERGE Marial**, engineering student at French Engineering School ECE
-- **ESCRIVA Mathis**, engineering student at French Engineering School ECE
-- **LALAIN Youri**, engineering student at French Engineering School ECE
-- **RAGE LILIAN**, engineering student at French Engineering School ECE
-- **HUVELLE Baptiste**, engineering student at French Engineering School ECE 
-
-Under the supervision of:
-- **Andre-Louis Rochet**, Lecturer at ECE & Co-Founder of TW3 Partners
-- **Paul Lemaistre**, CTO of TW3 Partners
-
-With the contribution of:
-- **ECE engineering school** as sponsor and financial contributor
-- **François STEPHAN** as director of ECE
-- **Gérard REUS** as acting director of iLAB
-- **Matthieu JOLLARD** ECE Alumni
-- **Louis GARCIA** ECE Alumni
-
-### Supervisory structure
-The iLab (intelligence Lab) is a structure created by the ECE and dedicated to artificial intelligence
-
-### About ECE
-ECE, a multi-program, multi-campus, and multi-sector engineering school specializing in digital engineering, trains engineers and technology experts for the 21st century, capable of meeting the challenges of the dual digital and sustainable development revolutions.
-
-
-**ECE-TRIOMPHANT-2.1-YL-72B-SLERP-V1** est un modèle de langage fusionné créé à partir des modèles **Sakalti/ultiima-72B** et **MaziyarPanahi/calme-3.2-instruct-78b**. Grâce à la méthode **SLERP (Spherical Linear Interpolation)**, il combine les forces des deux architectures pour offrir des performances optimales sur des tâches complexes de traitement du langage naturel (NLP).
+**rombodawg-Rombos-LLM-V2.5-Qwen-32b-Sakalt-Ultiima-32B-SLERP-V1** est un modèle de langage fusionné développé à l'ECE (École d'Ingénieurs) en utilisant la méthode de fusion **SLERP (Spherical Linear Interpolation)**. Ce modèle combine les forces des architectures **rombodawg/Rombos-LLM-V2.5-Qwen-32b** et **Sakalti/ultiima-32B** pour offrir des performances optimisées sur des tâches complexes de traitement du langage naturel (NLP).
 
 ## **Caractéristiques**
 - **Méthode de fusion :** SLERP (Spherical Linear Interpolation).
 - **Modèles sources :**
-  - [Sakalti/ultiima-72B](https://huggingface.co/Sakalti/ultiima-72B)
-  - [MaziyarPanahi/calme-3.2-instruct-78b](https://huggingface.co/MaziyarPanahi/calme-3.2-instruct-78b)
-- **Points forts :**
-  - Performances améliorées sur des tâches multi-domaines et de raisonnement.
-  - Capacité de traitement étendue grâce à la fusion des couches critiques.
-  - Optimisation en **bfloat16** pour des calculs rapides et efficaces.
-- **Applications cibles :**
+  - **rombodawg/Rombos-LLM-V2.5-Qwen-32b**
+  - **Sakalti/ultiima-32B**
+- **Optimisation :** bfloat16 pour des calculs rapides et efficaces.
+- **Applications :**
   - Raisonnement mathématique.
   - Compréhension contextuelle.
   - Tâches instructives (Instruction Following).
 
 ## **Configuration**
+
 ```yaml
 slices:
   - sources:
-      - model: MaziyarPanahi/calme-3.2-instruct-78b
-        layer_range: [0, 80]  # Limité à 80 couches
-      - model: Sakalti/ultiima-72B
-        layer_range: [0, 80]  # Correspondance avec le 78B
-merge_method: slerp
-base_model: MaziyarPanahi/calme-3.2-instruct-78b
+      - model: rombodawg/Rombos-LLM-V2.5-Qwen-32b
+        layer_range: [0, 64]
+      - model: Sakalti/ultiima-32B
+        layer_range: [0, 64]
+    merge_method: slerp
+base_model: rombodawg/Rombos-LLM-V2.5-Qwen-32b
 parameters:
   t:
     - filter: self_attn
@@ -69,5 +42,4 @@ parameters:
     - filter: mlp
       value: [1, 0.75, 0.5, 0.25, 0]
     - value: 0.5
-dtype: bfloat16
-```
+dtype: bfloat16