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Model: URajinda/ShweYon-V3-Base
Source: Original Platform

.gitattributes

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+*.pt filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+language:
+- my
+license: apache-2.0
+base_model: Qwen/Qwen2.5-1.5B
+tags:
+- text-generation
+- myanmar
+- shweyon
+- base-model
+- custom-tokenizer
+library_name: transformers
+---
+
+# 🐰 ShweYon-V3-Base (ရွှေယုန်-V3)
+
+**ShweYon-V3-Base** သည် Qwen 2.5 1.5B ကို အခြေခံ၍ မြန်မာဘာသာစကားအတွက် အထူးပြုပြင်ထားသော **Base Model** ဖြစ်ပါသည်။ ဤ Version တွင် ယခင် Version များကဲ့သို့ Tokenizer သီးခြားသုံးရန် မလိုတော့ဘဲ Model ၏ Embedding ထဲသို့ မြန်မာတုံကင်များကို တိုက်ရိုက်ပေါင်းစပ်ထားပါသည်။
+ShweYon-V3-Base is a Myanmar-centric base language model built on top of the Qwen 2.5 1.5B architecture. This model is a milestone in the "ShweYon" project, focusing on improving the efficiency of Myanmar script processing through a custom tokenizer.
+
+
+## 🎯 Purpose (ရည်ရွယ်ချက်)
+ဤ Model သည် မြန်မာဘာသာစကားအတွက် **Foundation Base Model** တစ်ခုအဖြစ် ရည်ရွယ်ပါသည်။ ဤ Model ကို အခြေခံ၍ Chatbot များ၊ Question Answering စနစ်များနှင့် အခြားသော Downstream NLP Task များအတွက် ထပ်မံ၍ Fine-tuning (SFT/RLHF) ပြုလုပ်ရန် အကောင်းဆုံး အုတ်မြစ်ဖြစ်ပါသည်။
+
+## ✨ Technical Highlights
+* **Integrated Tokenizer:** မြန်မာဝိဘတ်များနှင့် စကားလုံးပေါင်း ၉,၀၀၀ ကျော် ပါဝင်သော Custom Tokenizer ကို တစ်ပါတည်း ထည့်သွင်းထားပါသည်။
+* **Extended Vocabulary:** Vocabulary Size ကို `160,746` အထိ တိုးမြှင့်ထားသဖြင့် မြန်မာစာသားများကို ပိုမိုကျစ်လျစ်စွာနှင့် မြန်ဆန်စွာ တွက်ချက်နိုင်ပါသည်။
+* **Base Training:** မြန်မာစာပေ စာအုပ်များစွာဖြင့် Model ၏ မြန်မာစာ အခြေခံဗဟုသုတ ပိုမိုကောင်းမွန်လာစေရန် လေ့ကျင့်ပေးထားပါသည်။
+
+
+
+## 🚀 Quick Start
+ဤ Base Model ကို အောက်ပါအတိုင်း ခေါ်ယူအသုံးပြုနိုင်ပါသည်။
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "URajinda/ShweYon-V3-Base"
+
+# မျက်မှန်ရော ဦးနှောက်ရော တစ်ခါတည်း ပါလာပါမည်
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# စမ်းသပ်ကြည့်ရန်
+prompt = "မြန်မာနိုင်ငံ၏ သမိုင်းကြောင်းမှာ"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=32)
+print(tokenizer.decode(outputs[0]))
+
+⚠️ Note
+ဤ Model သည် Base Model သာ ဖြစ်သောကြောင့် လူသားနှင့် စကားပြောဆိုရန် (Instruction Following) အတွက် ထပ်မံ၍ Chat Fine-tuning လုပ်ရန် လိုအပ်ပါသေးသည်။
+
+⚖️ License
+Apache License 2.0

chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are a helpful assistant.' }}
+    {%- endif %}
+    {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
+    {%- else %}
+        {{- '<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

config.json

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+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "dtype": "bfloat16",
+  "eos_token_id": 151643,
+  "hidden_act": "silu",
+  "hidden_size": 1536,
+  "initializer_range": 0.02,
+  "intermediate_size": 8960,
+  "layer_types": [
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 131072,
+  "max_window_layers": 28,
+  "model_type": "qwen2",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 2,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "transformers_version": "4.57.3",
+  "use_cache": true,
+  "use_mrope": false,
+  "use_sliding_window": false,
+  "vocab_size": 160746
+}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "max_new_tokens": 2048,
+  "transformers_version": "4.57.3"
+}

model.safetensors

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+oid sha256:a809ba3400952699da09b8cc58b3b63507f1c564f1a3b8a107a662096d0dae6d
+size 3114531472

special_tokens_map.json

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+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "eos_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

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+size 13114316