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README.md

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 ---
-license: apache-2.0
+base_model: []
+library_name: transformers
 tags:
+- mergekit
 - merge
+
 ---
 
- 
-# Excalibur-7B
+
+# Excalibur-7b
 
 <img src="https://i.imgur.com/viIO4WT.png" width="550"/>
 
 <i>Image generated by Envoid's [Model9](https://huggingface.co/Envoid/model9)</i>
 
+[Magic-Dolphin-7b](https://huggingface.co/InferenceIllusionist/Magic-Dolphin-7b) was an unexpected surprise. Profoundly satisfied with it as a first attempt. For this follow-up I wanted to target the MMLU benchmark specifically.
+The challenge this time was placing more weight on Merlinite-7b as an unknown quantity that hasn't been in the spotlight despite its novel LAB tuning method.
+
+<b>Excalibur-7b</b> builds on past success and is the culimation of several learnings:
+* Measuring KL-divergences for new quantization types brought a deeper understanding of benchmarking and assessing model performance
+* This signifcantly sped up the testing process by using MMLU as a base, narrowing down over 10 candidate linear merges to 1: merliniteX-blockB1
+* Reaching the limitations of linear merging necessitated a pivot to reviewing the viability of SLERP, dares-ties, and passthrough methods
+* Thus a competing candidate merge pool was tested between different merge alogrithms. Once more the list was narrowed from 10 candidates to 1: merliniteX-blockF2
+* merliniteX-blockF2 (SLERP of Magic-Dolphin-7B and jaskier-7b-dpo in unorthadox proportions) was originally planned for release earlier this week
+* Instead -blockB1 and -blockF2 were merged and the results were placed head to head in a final round of tests. Ultimately a more conventional execution of SLERP showed the best results
+
+
+
+# output
+
+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:
+* models/merliniteX-blockB1
+* models/merliniteX-blockF2
 
+### Configuration
 
+The following YAML configuration was used to produce this model:
 
+```yaml
+slices:
+  - sources:
+      - model: models/merliniteX-blockF2
+        layer_range: [0, 32]
+      - model: models/merliniteX-blockB1
+        layer_range: [0, 32]
+# or, the equivalent models: syntax:
+# models:
+#   - model: psmathur/orca_mini_v3_13b
+#   - model: garage-bAInd/Platypus2-13B
+merge_method: slerp
+base_model: models/merliniteX-blockF2
+parameters:
+  t:
+    - filter: self_attn
+      value: [1, 0.7, 0.3, 0.5, 0]
+    - filter: mlp
+      value: [0, 0.3, 0.7, 0.5, 1]
+    - value: 0.5 # fallback for rest of tensors
+dtype: float16
 
-<h2>Model card coming soon.</h2>
+```

config.json

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+{
+  "_name_or_path": "models/merliniteX-blockF2",
+  "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": "float16",
+  "transformers_version": "4.37.1",
+  "use_cache": true,
+  "vocab_size": 32000
+}

mergekit_config.yml

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+slices:
+  - sources:
+      - model: models/merliniteX-blockF2
+        layer_range: [0, 32]
+      - model: models/merliniteX-blockB1
+        layer_range: [0, 32]
+# or, the equivalent models: syntax:
+# models:
+#   - model: psmathur/orca_mini_v3_13b
+#   - model: garage-bAInd/Platypus2-13B
+merge_method: slerp
+base_model: models/merliniteX-blockF2
+parameters:
+  t:
+    - filter: self_attn
+      value: [1, 0.7, 0.3, 0.5, 0]
+    - filter: mlp
+      value: [0, 0.3, 0.7, 0.5, 1]
+    - value: 0.5 # fallback for rest of tensors
+dtype: float16

model-00001-of-00002.safetensors

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model-00002-of-00002.safetensors

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model.safetensors.index.json

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