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README.md

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 ---
 license: llama2
 ---
+
+# LM-cocktail 10.7B v1
+
+
+This is a 50%-50% model of the SOLAR model and meow.
+
+https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0
+
+https://huggingface.co/rishiraj/meow
+
+
+who rank #1 and #2 among models <13B in the https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard by 2023/12/20.
+
+
+# Code
+
+The LM-cocktail is novel technique for merging multiple models https://arxiv.org/abs/2311.13534
+
+Code is backed up by this repo https://github.com/FlagOpen/FlagEmbedding.git
+
+Merging scripts available under the [./scripts](./scripts) folder
+
+
+# Result
+
+The SOLAR model is the first model <30B that can answer this question from my test:
+
+```
+What will AI be like in the year 1010 A.D?
+```
+
+without hullicinating into 1010 A.D is a future time (like other llama2 models)
+
+Models greater than that, like Yi-34B could answer this paradoxic question correctly as well, since it is huge enough.
+
+### SOLAR 10.7B output
+
+![img](./assets/SOLAR.png)
+
+### LMCocktail 10.7B output1
+
+![img](./assets/SOLAR_mixed.png)
+
+### LMCocktail 10.7B output2
+
+![img](./assets/SOLAR_mixed2.png)

config.json

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+{
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+  "architectures": [
+    "LlamaForCausalLM"
+  ],
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+  "model_type": "llama",
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+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.36.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}

generation_config.json

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+  "pad_token_id": 2,
+  "transformers_version": "4.36.2",
+  "use_cache": false
+}

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+    "model.norm.weight": "model-00005-of-00005.safetensors"
+  }
+}

sciprts/convert.py

@@ -0,0 +1,13 @@
+from transformers import AutoModelForCausalLM
+import torch
+import torch.utils.dlpack
+
+# Load the original model
+model_name = "./mixed_llm"
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Convert the model to a different precision
+model = model.half()
+
+# Save the model as a safetensor
+model.save_pretrained(f"./mixed_llm_half", safetensors=True)

sciprts/merge.py

@@ -0,0 +1,22 @@
+from LM_Cocktail import mix_models_by_layers
+import argparse
+
+if __name__ == "__main__":
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--model_type", type=str, default="decoder", help="Type of model to be mixed")
+    parser.add_argument("--output_path", type=str, default="./mixed_llm", help="Path to save the mixed model")
+    parser.add_argument("--max_length", type=int, default=100, help="Maximum length of the sequence to be generated")
+    parser.add_argument("--models", type=str, nargs='+', default=["meta-llama/Llama-2-7b-chat-hf", "Shitao/llama2-ag-news"], help="Path to the models to be mixed")
+    parser.add_argument("--weights", type=float, nargs='+', default=[0.7, 0.3], help="Weights of the models to be mixed")
+    parser.add_argument("--save_precision", type=str, default='float32', help="mixed model saved format")
+    args = parser.parse_args()
+
+    # Mix Large Language Models (LLMs) and save the combined model to the path: ./mixed_llm
+    model = mix_models_by_layers(
+        model_names_or_paths=args.models, 
+        model_type=args.model_type, 
+        weights=args.weights, 
+        output_path=args.output_path)
+
+    print(model)

sciprts/merge.sh

@@ -0,0 +1,8 @@
+#!/bin/bash
+eval "$(conda shell.bash hook)"
+conda activate llmcocktail
+
+CUDA_VISIBLE_DEVICES=1 python merge.py \
+    --models /media/hangyu5/Home/Documents/Hugging-Face/LM_cocktail/meow /media/hangyu5/Home/Documents/Hugging-Face/LM_cocktail/SOLAR-10.7B-Instruct-v1.0 \
+    --weights 0.5 0.5 \
+    |& tee ./merge.log

special_tokens_map.json

@@ -0,0 +1,30 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
+size 493443

tokenizer_config.json

@@ -0,0 +1,43 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [],
+  "bos_token": "<s>",
+  "chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{% if message['content']%}{{'### System:\n' + message['content']+'\n\n'}}{% endif %}{% elif message['role'] == 'user' %}{{'### User:\n' + message['content']+'\n\n'}}{% elif message['role'] == 'assistant' %}{{'### Assistant:\n'  + message['content']}}{% endif %}{% if loop.last and add_generation_prompt %}{{ '### Assistant:\n' }}{% endif %}{% endfor %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": true,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "</s>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": true
+}