Initial commit: Upload model card

README.md

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+---
+license: apache-2.0
+tags:
+- merge
+- mergekit
+- lazymergekit
+- llm-merge-cc4
+- OpenPipe/mistral-ft-optimized-1218
+- mlabonne/NeuralHermes-2.5-Mistral-7B
+- OpenPipe/mistral-ft-optimized-1218
+- mlabonne/NeuralHermes-2.5-Mistral-7B
+---
+
+# LLM_MERGE_CC4
+
+LLM_MERGE_CC4 est une fusion des modèles suivants créée par ManoloPueblo utilisant [mergekit](https://github.com/cg123/mergekit):
+* [OpenPipe/mistral-ft-optimized-1218](https://huggingface.co/OpenPipe/mistral-ft-optimized-1218)
+* [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B)
+
+## 🧩 Configuration de la fusion
+```yaml
+merge_method: passthrough
+slices:
+  - sources:
+    - model: OpenPipe/mistral-ft-optimized-1218
+      layer_range: [0, 32]
+  - sources:
+    - model: mlabonne/NeuralHermes-2.5-Mistral-7B
+      layer_range: [24, 32]
+merge_method: passthrough
+dtype: bfloat16
+```
+
+## Description
+LLM_MERGE_CC4 est un modèle de langage créé par la fusion de deux modèles Mistral :
+1. OpenPipe/mistral-ft-optimized-1218 - Le modèle de base Llama (modèle de référence) - (layer_range: [0, 32])
+2. mlabonne/NeuralHermes-2.5-Mistral-7B - Version optimisée par OpenPipe (layer_range: [24, 32])
+
+Cette fusion utilise la méthode "passthrough" avec normalisation et une précision float16 pour combiner les forces des deux modèles.
+
+## Architecture
+Le modèle conserve l'architecture de base de OpenPipe/mistral-ft-optimized-1218 tout en incorporant les améliorations des deux versions à travers une fusion pondérée.
+
+## Paramètres de fusion
+- Méthode de fusion : passthrough
+- Normalisation : activée
+- Type de données : float16
+- Densités et poids :
+  * OpenPipe/mistral-ft-optimized-1218 :   layer_range: [0, 32]
+  * NeuralHermes-2.5-Mistral-7B : layer_range: [24, 32]
+
+## Utilisation
+Ce modèle peut être utilisé avec la bibliothèque transformers de Hugging Face :
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+tokenizer = AutoTokenizer.from_pretrained("ManoloPueblo/LLM_MERGE_CC4")
+model = AutoModelForCausalLM.from_pretrained("ManoloPueblo/LLM_MERGE_CC4")
+```
+
+## Modèles fusionnés
+1. [OpenPipe/mistral-ft-optimized-1218](https://huggingface.co/OpenPipe/mistral-ft-optimized-1218) - Modèle de base
+2. [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B) - Version optimisée
+
+## Limitations
+Comme pour tout modèle de langage, les utilisateurs doivent être conscients des biais potentiels et des limitations inhérentes aux modèles sources. Les performances peuvent varier selon les cas d'utilisation.

config.json

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+{
+  "_name_or_path": "OpenPipe/mistral-ft-optimized-1218",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 40,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.46.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}

mergekit_config.yml

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+
+
+slices:
+  - sources:
+    - model: OpenPipe/mistral-ft-optimized-1218
+      layer_range: [0, 32]
+  - sources:
+    - model: mlabonne/NeuralHermes-2.5-Mistral-7B
+      layer_range: [24, 32]
+merge_method: passthrough
+dtype: bfloat16

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