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Model: wongwian-org/wongwian-micro-instruct
Source: Original Platform

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README.md

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+---
+license: mit
+language:
+  - th
+  - en
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+  - thai
+  - instruct
+  - causal-lm
+  - llama-architecture
+  - sentencepiece
+  - wongwian
+base_model: wongwian-org/wongwian-micro-instruct
+model_type: llama
+---
+
+<p align="center">
+  <img src="./ProfilePic.png" width="20%"/>
+</p>
+
+
+# Wongwian Micro Instruct — 272M
+
+**The first model in the Wongwian series.** A compact 272M-parameter Thai-centric language model trained entirely from scratch on 40B tokens of Thai-dominant data and then instruction-fine-tuned. No base weights from existing open models were used at any stage.
+
+> _"Cultural & Localization AI for the world"_ — Wongwian
+
+---
+# Wongwian Micro Instruct — 272M (ภาษาไทย)
+
+**โมเดลตัวแรกในซีรีส์ Wongwian** เป็นโมเดลภาษาขนาดเล็ก 272 ล้านพารามิเตอร์ที่เน้นภาษาไทยเป็นหลัก **ฝึกขึ้นมาจากศูนย์ (train from scratch) บนข้อมูล 40 พันล้าน token** แล้วผ่านการ instruction fine-tuning โดยไม่ได้นำ open weights ของโมเดลอื่นมาต่อยอดแต่อย่างใด
+
+> _"Cultural & Localization AI for the world"_ — Wongwian
+
+---
+
+## ภาพรวมโมเดล
+
+| คุณสมบัติ | ค่า |
+|---|---|
+| **ตระกูล** | Wongwian |
+| **ซีรีส์** | Micro |
+| **เวอร์ชัน** | Instruct v1 (step 450) |
+| **สถาปัตยกรรม** | LlamaForCausalLM |
+| **จำนวนพารามิเตอร์** | ~272 ล้าน |
+| **Context length** | 2,048 tokens |
+| **Precision** | bfloat16 |
+| **Token ที่ใช้ pre-train** | ~40 พันล้าน |
+| **ภาษาหลัก** | ไทย 🇹🇭 |
+| **ภาษารอง** | อังกฤษ 🇬🇧 |
+| **License** | MIT |
+
+---
+
+## เกี่ยวกับ Wongwian
+
+Wongwian คือโครงการวิจัย AI ภาษาไทยที่มุ่งสร้าง **โมเดลภาษา AI ที่มีประสิทธิภาพสูงและเข้าใจบริบทเชิงวัฒนธรรม** สำหรับภาษาไทยและภาษาอื่น ๆ ที่ขาดแคลนทรัพยากร โครงการนี้แสดงให้เห็นว่าโมเดล AI ที่มีคุณภาพสูงไม่จำเป็นต้องมีพารามิเตอร์มหาศาล โมเดลขนาดเล็กที่ออกแบบอย่างพิถีพิถันและใช้ข้อมูลที่เหมาะสม สามารถตอบโจทย์การใช้งานจริงได้อย่างมีประสิทธิผล
+
+**วิสัยทัศน์:** _Cultural & Localization AI for the world_ — สร้าง AI ที่เข้าใจความละเอียดอ่อนทางภาษา วัฒนธรรม และบริบทของแต่ละชุมชนอย่างลึกซึ้ง
+
+**จุดแข็งของโมเดลนี้:**
+
+- **ฝึกจากศูนย์ (from scratch)** บนข้อมูลภาษาไทยเป็นหลัก ไม่ได้ต่อยอดจากโมเดลสาธารณะใดทั้งสิ้น
+- **SentencePiece Unigram tokenizer** (32K vocab) ออกแบบมาเฉพาะสำหรับโครงสร้างภาษาไทยและข้อความผสมไทย-อังกฤษ
+- สร้างบนเฟรมเวิร์ค [OLMo-core](https://github.com/allenai/OLMo-core) แบบ open-source
+- ผ่านการ instruction fine-tuning (SFT) ด้วยข้อมูลบทสนทนาภาษาไทย
+- รูปแบบ prompt สะท้อนการโต้ตอบผู้ช่วยภาษาไทยอย่างเป็นธรรมชาติ
+
+---
+
+## Model Overview
+
+| Property | Value |
+|---|---|
+| **Model family** | Wongwian |
+| **Series** | Micro |
+| **Version** | Instruct v1 (step 450) |
+| **Architecture** | LlamaForCausalLM |
+| **Parameters** | ~272 M |
+| **Context length** | 2 048 tokens |
+| **Precision** | bfloat16 |
+| **Pre-train tokens** | ~40 B |
+| **Primary language** | Thai 🇹🇭 |
+| **Secondary language** | English 🇬🇧 |
+| **License** | MIT |
+
+---
+
+## About Wongwian
+
+Wongwian is a Thai AI research initiative focused on building **efficient, culturally-grounded language models** for Thai and other under-resourced languages. The project demonstrates that high-quality language AI does not require massive parameter counts — a carefully designed small model, trained on the right data, can serve real-world use cases effectively.
+
+**Vision:** _Cultural & Localization AI for the world_ — delivering language models that deeply understand the cultural, linguistic, and contextual nuances of each community they serve.
+
+**What makes this model different:**
+
+- Trained **from scratch** on Thai-dominant data — not a fine-tune of any existing public model
+- Custom **SentencePiece Unigram** tokenizer (32K vocab) designed for Thai morphology and mixed Thai-English text
+- Built on the open [OLMo-core](https://github.com/allenai/OLMo-core) training framework
+- Full instruction fine-tuning (SFT) with Thai conversation data
+- Chat prompt format mirrors natural Thai assistant interaction
+
+---
+
+## Quick Start
+
+### pip install
+
+```bash
+pip install transformers sentencepiece
+```
+
+### Chat generation (recommended)
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "wongwian-org/wongwian-micro-instruct"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id, use_fast=True)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+model.eval()
+
+messages = [
+    {"role": "user", "content": "สวัสดี อธิบาย AI ให้ฟังหน่อย"},
+]
+
+input_ids = tokenizer.apply_chat_template(
+    messages,
+    tokenize=True,
+    add_generation_prompt=True,
+    return_tensors="pt",
+)
+with torch.no_grad():
+    output = model.generate(
+        input_ids.to(model.device),
+        max_new_tokens=200,
+        do_sample=True,
+        temperature=0.7,
+        top_p=0.9,
+        repetition_penalty=1.3,
+        no_repeat_ngram_size=4,
+        eos_token_id=tokenizer.eos_token_id,
+        pad_token_id=tokenizer.pad_token_id,
+    )
+new_tokens = output[0, input_ids.shape[1]:]
+print(tokenizer.decode(new_tokens, skip_special_tokens=True))
+```
+
+### Multi-turn conversation
+
+```python
+history = []
+
+def chat(user_message: str, system_prompt: str | None = None) -> str:
+    messages = []
+    if system_prompt:
+        messages.append({"role": "system", "content": system_prompt})
+    messages.extend(history)
+    messages.append({"role": "user", "content": user_message})
+
+    input_ids = tokenizer.apply_chat_template(
+        messages,
+        tokenize=True,
+        add_generation_prompt=True,
+        return_tensors="pt",
+    )
+    with torch.no_grad():
+        output = model.generate(
+            input_ids.to(model.device),
+            max_new_tokens=200,
+            do_sample=True,
+            temperature=0.7,
+            top_p=0.9,
+            repetition_penalty=1.3,
+            no_repeat_ngram_size=4,
+            eos_token_id=tokenizer.eos_token_id,
+            pad_token_id=tokenizer.pad_token_id,
+        )
+    reply = tokenizer.decode(output[0, input_ids.shape[1]:], skip_special_tokens=True).strip()
+    history.append({"role": "user", "content": user_message})
+    history.append({"role": "assistant", "content": reply})
+    return reply
+
+print(chat("สวัสดี คุณคือใคร?"))
+print(chat("แล้วคุณทำอะไรได้บ้าง?"))
+```
+
+### Chat template format
+
+The model uses the following plain-text prompt format (applied automatically by `apply_chat_template`):
+
+```
+<s>system: <system_prompt>
+ผู้ใช้: <user_turn>
+ผู้ช่วย: <assistant_turn></s>
+ผู้ใช้: <user_turn>
+ผู้ช่วย:
+```
+
+---
+
+## Prompt Engineering Tips
+
+| Tip | Detail |
+|---|---|
+| **Temperature** | 0.6 – 0.8 for natural Thai conversation |
+| **Repetition penalty** | 1.2 – 1.4 — recommended; prevents looping |
+| **no_repeat_ngram_size** | 4 — prevents phrase repetition |
+| **max_new_tokens** | 150 – 300 for chat; 512 for long-form |
+| **System prompt** | Optional but improves role adherence |
+
+---
+
+## Limitations
+
+- **Size:** At 272M parameters, this model is suited for assistive tasks and demonstrations, not advanced reasoning or complex long-form analysis.
+- **Hallucination:** Like all language models, the model may produce inaccurate information. Always verify critical outputs.
+- **Context length:** Maximum 2 048 tokens per call; performance may degrade near the limit.
+- **Bias:** The model may reflect biases present in the training corpus.
+
+---
+
+## Citation
+
+```bibtex
+@misc{wongwian2026micro,
+  title  = {Wongwian Micro Instruct: A Thai-Centric Small Language Model Trained from Scratch},
+  author = {Wongwian AI Research},
+  year   = {2026},
+  url    = {https://huggingface.co/wongwian-org/wongwian-micro-instruct}
+}
+```
+
+---

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "model_type": "llama",
+  "hidden_size": 1024,
+  "intermediate_size": 2816,
+  "num_attention_heads": 8,
+  "num_hidden_layers": 16,
+  "num_key_value_heads": 8,
+  "vocab_size": 32000,
+  "hidden_act": "silu",
+  "max_position_embeddings": 2048,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000,
+  "tie_word_embeddings": false,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "pad_token_id": 3,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.40.0"
+}

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special_tokens_map.json

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+{
+  "bos_token": "<s>",
+  "eos_token": "</s>",
+  "unk_token": "<unk>",
+  "pad_token": "<pad>"
+}

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tokenizer_config.json

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+{
+  "backend": "tokenizers",
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "model_max_length": 2048,
+  "pad_token": "<pad>",
+  "tokenizer_class": "TokenizersBackend",
+  "unk_token": "<unk>",
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}system: {{ message['content'] }}\n{% elif message['role'] == 'user' %}User: {{ message['content'] }}\n{% elif message['role'] == 'assistant' %}Assistant: {{ message['content'] }}\n{{ eos_token }}{% endif %}{% endfor %}{% if add_generation_prompt %}Assistant:{% endif %}"
+}