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Model: Mihaiii/dolphin-2.6-mistral-7b-dpo-5.93B
Source: Original Platform

.gitattributes

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README.md

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+---
+datasets:
+- ehartford/dolphin
+- jondurbin/airoboros-2.2.1
+- ehartford/dolphin-coder
+- teknium/openhermes
+- ise-uiuc/Magicoder-OSS-Instruct-75K
+- ise-uiuc/Magicoder-Evol-Instruct-110K
+- LDJnr/Capybara
+language:
+- en
+license: apache-2.0
+---
+
+This is a pruned version of [cognitivecomputations/dolphin-2.6-mistral-7b-dpo](https://huggingface.co/cognitivecomputations/dolphin-2.6-mistral-7b-dpo) from 7.24B params to 5.93B params (~ 82%).
+
+# Steps to replicate:
+
+Use [laserQlora.ipynb](https://github.com/cognitivecomputations/laserRMT/blob/main/laserQlora.ipynb) from [cognitivecomputations/laserRMT](https://github.com/cognitivecomputations/laserRMT) to determine which layers should be eliminated.
+
+Replace `model_name = "mistralai/Mistral-7B-v0.1"` with `model_name = "cognitivecomputations/dolphin-2.6-mistral-7b-dpo"`.
+I also ran the script only for `self_attn.v_proj` (so change the script to `layer_types=["self_attn.v_proj"]`)
+
+Order by snr descending and eliminate top layers using [mergekit](https://github.com/arcee-ai/mergekit).
+The threshold for elimination is up to you, depeding on how many layers you want removed. I decided to remove 6 layers (indexes: 3, 5, 16, 18, 19, 24 )
+
+Here is the mergekit config:
+```yml
+slices:
+  - sources:
+    - model: "cognitivecomputations/dolphin-2.6-mistral-7b-dpo"
+      layer_range: [0, 3]
+  - sources:
+    - model: "cognitivecomputations/dolphin-2.6-mistral-7b-dpo"
+      layer_range: [4, 5]
+  - sources:
+    - model: "cognitivecomputations/dolphin-2.6-mistral-7b-dpo"
+      layer_range: [6, 16]
+  - sources:
+    - model: "cognitivecomputations/dolphin-2.6-mistral-7b-dpo"
+      layer_range: [17, 18]
+  - sources:
+    - model: "cognitivecomputations/dolphin-2.6-mistral-7b-dpo"
+      layer_range: [20, 24]
+  - sources:
+    - model: "cognitivecomputations/dolphin-2.6-mistral-7b-dpo"
+      layer_range: [25, 32]
+merge_method: passthrough
+dtype: bfloat16
+```
+
+The model outputted by mergekit with this configuration is this model (dolphin-2.6-mistral-7b-dpo-5.93B).

added_tokens.json

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+{
+  "<|im_start|>": 32000
+}

config.json

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+{
+  "_name_or_path": "dolphin-2.6-mistral-7b-dpo-pruned",
+  "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": 26,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.38.1",
+  "use_cache": false,
+  "vocab_size": 32001
+}

generation_config.json

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+{
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+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.38.1",
+  "use_cache": false
+}

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special_tokens_map.json

@@ -0,0 +1,30 @@
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