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Model: voidful/Llama-3.1-TAIDE-R1-8B-Chat
Source: Original Platform

.gitattributes

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+tokenizer_config.json filter=lfs diff=lfs merge=lfs -text

.ipynb_checkpoints/special_tokens_map-checkpoint.json

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+{
+  "bos_token": {
+    "content": "<|begin_of_text|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|eot_id|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

.ipynb_checkpoints/tokenizer-checkpoint.json

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README.md

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+---
+base_model:
+- deepseek-ai/DeepSeek-R1-Distill-Llama-8B
+- taide/Llama-3.1-TAIDE-LX-8B-Chat
+- meta-llama/Llama-3.1-8B-Instruct
+library_name: transformers
+tags:
+- mergekit
+- merge
+
+---
+# voidful/Llama-3.1-TAIDE-R1-8B-Chat
+
+This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
+
+## Usage
+
+```python
+import vllm
+from transformers import  AutoTokenizer
+from vllm import LLM, SamplingParams
+
+model_name = "voidful/Llama-3.1-TAIDE-R1-8B-Chat"
+llm = vllm.LLM(model=model_name,max_model_len=4096)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+messages = [
+  {"role": "user", "content": f"早餐喝早餐店的奶茶會導致烙賽為什麼?"},
+]
+prompts = tokenizer.apply_chat_template(
+    messages,
+    add_generation_prompt=True,
+    tokenize=False
+)
+
+sampling_params = SamplingParams(temperature=0.6, max_tokens=512, top_p=0.9)
+outputs = llm.generate(prompts, sampling_params)
+
+print(f"{prompts}")
+print(f"{outputs[0].outputs[0].text}\n")
+
+
+sampling_params = SamplingParams(temperature=0.6, max_tokens=512, top_p=0.9)
+outputs = llm.generate(prompts, sampling_params)
+
+print(f"{prompts}")
+print(f"{outputs[0].outputs[0].text}\n")
+```
+
+Output
+```
+<think> 關於「早餐喝早餐店的奶茶會導致烙賽」的問題，可能的原因有幾種可能的解釋。首先，「烙賽」這個詞在台灣的網路用語中，通常指的是「燒腸」或「拉肚子」的意思，指的是人體的腸胃或腸道發生不舒服的狀況，可能是消化不良、腹泻、或其他腸胃道的問題。所以，喝了不健康的飲料，可能會導致腸胃不舒服，引起「烙賽」的反應。 
+
+其次，一個可能的原因是，早餐店的奶茶可能使用了低品質的奶源、含糖或含奶精等添加物。奶精是一種人工添加劑，可能會對胃造成刺激或不舒服的感覺。再者，早餐的奶茶可能是用即溶的粉末或濃縮的奶來泡的，這些東西可能含有許多添加劑或不健康的成分。 
+
+最後，個人的體質也是一個因素。有人可能對奶或糖有過敏或不耐受的反應，喝了之後就會出現不舒服的症狀。 
+
+綜合上述的原因，早餐喝早餐店的奶茶可能會導致烙賽的原因有：使用低品質的奶源、含糖或奶精等添加劑、個人的體質對奶或糖有過敏或不耐受的反應等。 
+
+<answer> 早餐喝早餐店的奶茶可能導致烙賽的原因有低品質的奶源、含糖或奶精等添加劑、以及個人的體質對奶或糖有過敏或不耐受的反應等。這是因為不健康的飲料成分可能會對身體造成不舒服的影響。</answer>
+```
+
+## Merge Details
+### Merge Method
+
+This model was merged using the [SCE](https://arxiv.org/abs/2408.07990) merge method using [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) as a base.
+
+### Models Merged
+
+The following models were included in the merge:
+* [deepseek-ai/DeepSeek-R1-Distill-Llama-8B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-8B)
+* [taide/Llama-3.1-TAIDE-LX-8B-Chat](https://huggingface.co/taide/Llama-3.1-TAIDE-LX-8B-Chat)
+
+### Configuration
+
+The following YAML configuration was used to produce this model:
+
+```yaml
+merge_method: sce
+base_model: meta-llama/Llama-3.1-8B-Instruct
+tokenizer:
+  source: taide/Llama-3.1-TAIDE-LX-8B-Chat
+models:
+  - model: taide/Llama-3.1-TAIDE-LX-8B-Chat
+  - model: deepseek-ai/DeepSeek-R1-Distill-Llama-8B
+```

config.json

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+{
+  "_name_or_path": "meta-llama/Llama-3.1-8B-Instruct",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 8.0,
+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.49.0",
+  "use_cache": true,
+  "vocab_size": 188256
+}

configuration.json

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+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}

llama-3-1-TAIDE-R1-Chat.gguf

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+size 17053084576

mergekit_config.yml

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+merge_method: sce
+base_model: meta-llama/Llama-3.1-8B-Instruct
+tokenizer:
+  source: taide/Llama-3.1-TAIDE-LX-8B-Chat
+models:
+  - model: taide/Llama-3.1-TAIDE-LX-8B-Chat
+  - model: deepseek-ai/DeepSeek-R1-Distill-Llama-8B

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params

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+{
+  "stop": ["</answer>","<|start_header_id|>","<|end_header_id|>","<|eot_id|>"],
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "repeat_penalty": 1.1,
+  "num_ctx": 8192
+}

special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<|begin_of_text|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|eot_id|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

system

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+你是一個來自台灣的AI助理，你的名字是 TAIDE，樂於以台灣人的立場幫助使用者，會用繁體中文回答問題。
+You first think about the reasoning process in the mind and then provide the user with the answer while reasoning step by step, and putting the final answer within \\boxed{}.
+The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively, i.e.,
+<think> reasoning process here </think><answer> answer here </answer>.

template

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+{{- if or .System .Tools }}<|start_header_id|>system<|end_header_id|>
+{{- if .System }}
+
+{{ .System }}
+{{- end }}
+{{- if .Tools }}
+
+Cutting Knowledge Date: December 2023
+
+When you receive a tool call response, use the output to format an answer to the orginal user question.
+
+You are a helpful assistant with tool calling capabilities.
+{{- end }}<|eot_id|>
+{{- end }}
+{{- range $i, $_ := .Messages }}
+{{- $last := eq (len (slice $.Messages $i)) 1 }}
+{{- if eq .Role "user" }}<|start_header_id|>user<|end_header_id|>
+{{- if and $.Tools $last }}
+
+Given the following functions, please respond with a JSON for a function call with its proper arguments that best answers the given prompt.
+
+Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}. Do not use variables.
+
+{{ range $.Tools }}
+{{- . }}
+{{ end }}
+Question: {{ .Content }}<|eot_id|>
+{{- else }}
+
+{{ .Content }}<|eot_id|>
+{{- end }}{{ if $last }}<|start_header_id|>assistant<|end_header_id|>
+
+{{ end }}
+{{- else if eq .Role "assistant" }}<|start_header_id|>assistant<|end_header_id|>
+{{- if .ToolCalls }}
+{{ range .ToolCalls }}
+{"name": "{{ .Function.Name }}", "parameters": {{ .Function.Arguments }}}{{ end }}
+{{- else }}
+
+{{ .Content }}
+{{- end }}{{ if not $last }}<|eot_id|>{{ end }}
+{{- else if eq .Role "tool" }}<|start_header_id|>ipython<|end_header_id|>
+
+{{ .Content }}<|eot_id|>{{ if $last }}<|start_header_id|>assistant<|end_header_id|>
+
+{{ end }}
+{{- end }}
+{{- end }}

tokenizer.json

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