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README.md

@@ -1,22 +1,31 @@
 ---
-tags:
-- merge
-- mergekit
-- lazymergekit
-- yam-peleg/Experiment26-7B
-- cognitivecomputations/dolphin-2.8-experiment26-7b
 base_model:
 - yam-peleg/Experiment26-7B
 - cognitivecomputations/dolphin-2.8-experiment26-7b
+library_name: transformers
+tags:
+- mergekit
+- merge
+
 ---
+# merge
+
+This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
 
-# Dolphin-2.8-slerp
+## Merge Details
+### Merge Method
 
-Dolphin-2.8-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+This model was merged using the SLERP merge method.
+
+### Models Merged
+
+The following models were included in the merge:
 * [yam-peleg/Experiment26-7B](https://huggingface.co/yam-peleg/Experiment26-7B)
 * [cognitivecomputations/dolphin-2.8-experiment26-7b](https://huggingface.co/cognitivecomputations/dolphin-2.8-experiment26-7b)
 
-## 🧩 Configuration
+### Configuration
+
+The following YAML configuration was used to produce this model:
 
 ```yaml
 slices:
@@ -35,29 +44,5 @@ parameters:
       value: [1, 0.5, 0.7, 0.3, 0]
     - value: 0.5
 dtype: bfloat16
-```
-
-## 💻 Usage
 
-```python
-!pip install -qU transformers accelerate
-
-from transformers import AutoTokenizer
-import transformers
-import torch
-
-model = "pabloce/Dolphin-2.8-slerp"
-messages = [{"role": "user", "content": "What is a large language model?"}]
-
-tokenizer = AutoTokenizer.from_pretrained(model)
-prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
-pipeline = transformers.pipeline(
-    "text-generation",
-    model=model,
-    torch_dtype=torch.float16,
-    device_map="auto",
-)
-
-outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
-print(outputs[0]["generated_text"])
-```
+```

config.json

@@ -0,0 +1,26 @@
+{
+  "_name_or_path": "yam-peleg/Experiment26-7B",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "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": "bfloat16",
+  "transformers_version": "4.37.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}

mergekit_config.yml

@@ -0,0 +1,16 @@
+slices:
+  - sources:
+      - model: yam-peleg/Experiment26-7B
+        layer_range: [0, 32]
+      - model: cognitivecomputations/dolphin-2.8-experiment26-7b
+        layer_range: [0, 32]
+merge_method: slerp
+base_model: yam-peleg/Experiment26-7B
+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
+dtype: bfloat16

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