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README.md

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+---
+base_model: 
+- mistralai/Mistral-7B-v0.1
+library_name: transformers
+tags:
+- mergekit
+- merge
+- mistralai/Mistral-7B-v0.1
+- SanjiWatsuki/Kunoichi-DPO-v2-7B
+- maywell/PiVoT-0.1-Evil-a
+- mlabonne/ArchBeagle-7B
+- NeverSleep/Noromaid-7B-0.4-DPO
+
+---
+# konstanta-final
+
+This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
+
+## Merge Details
+### Merge Method
+
+This model was merged using the SLERP merge method.
+
+### Models Merged
+
+The following models were included in the merge:
+* [SanjiWatsuki/Kunoichi-DPO-v2-7B](https://huggingface.co/SanjiWatsuki/Kunoichi-DPO-v2-7B)
+* [maywell/PiVoT-0.1-Evil-a](https://huggingface.co/maywell/PiVoT-0.1-Evil-a)
+* [mlabonne/ArchBeagle-7B](https://huggingface.co/mlabonne/ArchBeagle-7B)
+* [NeverSleep/Noromaid-7B-0.4-DPO](https://huggingface.co/NeverSleep/Noromaid-7B-0.4-DPO)
+
+### Configuration
+
+The following YAML configuration was used to produce this model (to reproduce use mergekit-mega command):
+
+```yaml
+
+base_model: mistralai/Mistral-7B-v0.1
+dtype: float16
+merge_method: dare_ties
+parameters:
+  int8_mask: true
+slices:
+- sources:
+  - layer_range: [0, 32]
+    model: mistralai/Mistral-7B-v0.1
+  - layer_range: [0, 32]
+    model: : SanjiWatsuki/Kunoichi-DPO-v2-7B
+    parameters:
+      density: 0.8
+      weight: 0.5
+  - layer_range: [0, 32]
+    model: : maywell/PiVoT-0.1-Evil-a
+    parameters:
+      density: 0.3
+      weight: 0.15
+name: first-step
+---
+base_model: mistralai/Mistral-7B-v0.1
+dtype: float16
+merge_method: dare_ties
+parameters:
+  int8_mask: true
+slices:
+- sources:
+  - layer_range: [0, 32]
+    model: mistralai/Mistral-7B-v0.1
+  - layer_range: [0, 32]
+    model: mlabonne/ArchBeagle-7B
+    parameters:
+      density: 0.8
+      weight: 0.75
+  - layer_range: [0, 32]
+    model: LakoMoor/Silicon-Alice-7B
+    parameters:
+      density: 0.6
+      weight: 0.30
+name: second-step
+---
+models:
+   - model: first-step
+   - model: second-step
+merge_method: slerp
+base_model: first-step
+parameters:
+  t:
+    - filter: self_attn
+      value: [0, 0.5, 0.3, 0.7, 1]
+    - filter: mlp
+      value: [1, 0.5, 0.7, 0.3, 0]
+    - value: 0.5
+  int8_mask: true
+  normalize: true
+dtype: float16
+```

config.json

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+{
+  "_name_or_path": "Konstanta-V2-Alpha-7B",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "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": 32,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.35.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}

mergekit_config.yml

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+
+models:
+   - model: /content/drive/MyDrive/output_model2/konstanta-first-step
+   - model: /content/drive/MyDrive/output_model2/konstanta-second-step
+merge_method: slerp
+base_model: /content/drive/MyDrive/output_model2/konstanta-first-step
+parameters:
+  t:
+    - filter: self_attn
+      value: [0, 0.5, 0.3, 0.7, 1]
+    - filter: mlp
+      value: [1, 0.5, 0.7, 0.3, 0]
+    - value: 0.5 # fallback for rest of tensors
+  int8_mask: true
+  normalize: true
+dtype: float16

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