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README.md

@@ -1,31 +1,23 @@
 ---
+license: apache-2.0
 tags:
+- moe
+- frankenmoe
 - merge
 - mergekit
 - lazymergekit
 - argilla/CapybaraHermes-2.5-Mistral-7B
-- WizardLM/WizardMath-7B-V1.1
+- MediaTek-Research/Breeze-7B-Instruct-v0_1
 base_model:
 - argilla/CapybaraHermes-2.5-Mistral-7B
-- WizardLM/WizardMath-7B-V1.1
+- MediaTek-Research/Breeze-7B-Instruct-v0_1
 ---
 
-# 試製-暮光-4x7B
-
-試製-暮光-7B　是用[LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing)融合以下模型生成的：
-* [argilla/CapybaraHermes-2.5-Mistral-7B](https://huggingface.co/argilla/CapybaraHermes-2.5-Mistral-7B)
-* [WizardLM/WizardMath-7B-V1.1](https://huggingface.co/WizardLM/WizardMath-7B-V1.1)
-
-這是一個實驗模型，目的是爲了檢驗套用在不同語言上的高品質模型調教是否能夠轉移（此模型爲英文到中文）。
-
-
 # shizhi-twilight-7B
 
-shizhi-twilight-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+shizhi-twilight-7B is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
 * [argilla/CapybaraHermes-2.5-Mistral-7B](https://huggingface.co/argilla/CapybaraHermes-2.5-Mistral-7B)
-* [WizardLM/WizardMath-7B-V1.1](https://huggingface.co/WizardLM/WizardMath-7B-V1.1)
-
-This is an experiment product on checking whether high quality fine-tuning on one language (English) could be transferred to another language (Mandarin) leveraging Slerp merge method.
+* [MediaTek-Research/Breeze-7B-Instruct-v0_1](https://huggingface.co/MediaTek-Research/Breeze-7B-Instruct-v0_1)
 
 ## 🧩 Configuration
 
@@ -36,39 +28,42 @@ models:
   - model: argilla/CapybaraHermes-2.5-Mistral-7B
     parameters:
       density: 0.53
-      weight: 0.65
-  - model: WizardLM/WizardMath-7B-V1.1
-    parameters:
-      density: 0.53
-      weight: 0.35
+      weight: 0.95
 merge_method: dare_ties
 base_model: MediaTek-Research/Breeze-7B-Instruct-v0_1
 parameters:
   int8_mask: true
+  normalize: true
+experts:
+  - source_model: argilla/CapybaraHermes-2.5-Mistral-7B
+    positive_prompts:
+     - "Peform the following tasks with your best ability"
+  - source_model: MediaTek-Research/Breeze-7B-Instruct-v0_1
+    positive_prompts:
+     - "You are a helpful AI assistant built by MediaTek Research. The user you are helping speaks Traditional Chinese and comes from Taiwan."
 dtype: bfloat16
 ```
 
 ## 💻 Usage
 
 ```python
-!pip install -qU transformers accelerate
+!pip install -qU transformers bitsandbytes accelerate
 
 from transformers import AutoTokenizer
 import transformers
 import torch
 
 model = "lipcut/shizhi-twilight-7B"
-messages = [{"role": "user", "content": "什麼是大型語言模型?"}]
 
 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",
+    model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
 )
 
+messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
+prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
 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"])
 ```

added_tokens.json

@@ -0,0 +1,4 @@
+{
+  "<EOD>": 61873,
+  "<PAD>": 61874
+}

config.json

@@ -0,0 +1,31 @@
+{
+  "_name_or_path": "MediaTek-Research/Breeze-7B-Instruct-v0_1",
+  "architectures": [
+    "MixtralForCausalLM"
+  ],
+  "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": "mixtral",
+  "num_attention_heads": 32,
+  "num_experts_per_tok": 2,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "num_local_experts": 2,
+  "output_router_logits": false,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "router_aux_loss_coef": 0.001,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.37.2",
+  "use_cache": false,
+  "vocab_size": 61952
+}

mergekit_moe_config.yml

@@ -0,0 +1,21 @@
+
+models:
+  - model: MediaTek-Research/Breeze-7B-Instruct-v0_1
+    # No parameters necessary for base model
+  - model: argilla/CapybaraHermes-2.5-Mistral-7B
+    parameters:
+      density: 0.53
+      weight: 0.95
+merge_method: dare_ties
+base_model: MediaTek-Research/Breeze-7B-Instruct-v0_1
+parameters:
+  int8_mask: true
+  normalize: true
+experts:
+  - source_model: argilla/CapybaraHermes-2.5-Mistral-7B
+    positive_prompts:
+     - "Peform the following tasks with your best ability"
+  - source_model: MediaTek-Research/Breeze-7B-Instruct-v0_1
+    positive_prompts:
+     - "You are a helpful AI assistant built by MediaTek Research. The user you are helping speaks Traditional Chinese and comes from Taiwan."
+dtype: bfloat16

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special_tokens_map.json

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+{
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+    "rstrip": false,
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+    "normalized": false,
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tokenizer.model

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+size 911034

tokenizer_config.json

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+    "61873": {
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+      "single_word": false,
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+  "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'].strip() %}{% else %}{% set loop_messages = messages %}{% set system_message = 'You are a helpful AI assistant built by MediaTek Research. The user you are helping speaks Traditional Chinese and comes from Taiwan.' %}{% endif %}{{ bos_token }}{{ system_message }}   {% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/... or system/user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST] ' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + ' ' }}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}",
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+  "use_default_system_prompt": false
+}