初始化项目，由ModelHub XC社区提供模型

Model: KBTG-Labs/THaLLE-0.2-ThaiLLM-8B-fa Source: Original Platform
2026-05-05 02:59:18 +08:00
commit d7d1ffa6b6
14 changed files with 152331 additions and 0 deletions
--- a/README.md
+++ b/README.md
@@ -0,0 +1,117 @@
+---
+license: apache-2.0
+base_model:
+- ThaiLLM/ThaiLLM-8B
+- Qwen/Qwen3-8B
+- Qwen/Qwen3-8B-Base
+pipeline_tag: text-generation
+language:
+- en
+- th
+tags:
+- finance
+- mergekit
+- merge
+---
+# THaLLE-ThaiLLM: Domain-Specialized Small LLMs for Finance and Thai
+
+## Model Overview
+
+This 8B language model is developed as an extension of ThaiLLM-8B, with a focus on enhancing instruction-following capabilities and financial knowledge. The model is constructed using [mergekit](https://github.com/arcee-ai/mergekit) that integrates ThaiLLM-8B with Qwen3-8B and THaLLE, the latter of which was trained on 80 CFA examination sets.
+
+**THaLLE-0.2-ThaiLLM-8B-fa** has the following features:
+- **Supports switching between thinking and non-thinking modes**, similar to [Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B).
+- **Offers enhanced Thai language understanding** from [ThaiLLM-8B](https://huggingface.co/ThaiLLM/ThaiLLM-8B).
+- **Incorporates the financial knowledge and understanding** expected of THaLLE fine-tuning.
+
+## Usage
+
+### Requirements
+
+Since `KBTG-Labs/THaLLE-0.2-ThaiLLM-8B-fa` is a fine-tuned of Qwen3-8B you will need to install `transformers>=4.51.0`.
+
+### Running using Transformers
+
+Running the script below generates output based on the given input messages.
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+MODEL_ID: str = "KBTG-Labs/THaLLE-0.2-ThaiLLM-8B-fa"
+
+def inference(messages: list[dict[str, str]], model, tokenizer) -> str:
+    text = tokenizer.apply_chat_template(
+        messages,
+        tokenize=False,
+        add_generation_prompt=True,
+        enable_thinking=False, # Switches thinking modes.
+    )
+    model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
+
+    generated_ids = model.generate(
+        model_inputs.input_ids,
+        max_new_tokens=768,
+        do_sample=False,
+        temperature=None,
+        top_p=None,
+        top_k=None,
+        pad_token_id=tokenizer.eos_token_id,
+    )
+    generated_ids = [
+        output_ids[len(input_ids) :]
+        for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+    ]
+
+    response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+    return response
+
+if __name__ == "__main__":
+    tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
+    model = AutoModelForCausalLM.from_pretrained(
+        MODEL_ID,
+        torch_dtype=torch.bfloat16,
+        device_map="auto",
+    )
+
+    messages = [{"role": "user", "content": "สวัสดี!"}]
+    inference(messages, model, tokenizer)
+
+```
+
+## Results
+
+For more details, see our [Technical Report.](https://arxiv.org/abs/2601.04597)
+
+| Model                                   | M3 Exam   | M6 Exam   | Flare CFA* | IC        |
+| --------------------------------------- | --------- | --------- | ---------- | --------- |
+| Non-Thinking                            |           |           |            |           |
+| `Qwen3-8B`                              | 0.660     | 0.545     | 0.753      | 0.640     |
+| `ThaiLLM-8B-Instruct`**                 | 0.707     | **0.623** | 0.762      | **0.720** |
+| `THaLLE-0.2-ThaiLLM-8B-fa`              | **0.725** | 0.572     | **0.771**  | **0.720** |
+| Thinking                                |           |           |            |           |
+| `Qwen3-8B`                              | 0.706     | 0.590     | 0.806      | 0.600     |
+| `ThaiLLM-8B-Instruct`**                 | 0.720     | 0.661     | 0.820      | 0.720     |
+| `THaLLE-0.2-ThaiLLM-8B-fa`              | **0.779** | **0.678** | **0.852**  | **0.840** |
+
+[*] Flare CFA is `"TheFinAI/flare-cfa"`
+
+[**] `"ThaiLLM-8B-Instruct"` is [KBTG-Labs/ThaiLLM-8B-Instruct](https://huggingface.co/KBTG-Labs/ThaiLLM-8B-Instruct)
+
+[vLLM](https://github.com/vllm-project/vllm) was used for evaluations, results might vary.
+
+## Citation
+
+If you find our work useful, please cite:
+
+```
+@misc{labs2026thallethaillmdomainspecializedsmallllms,
+      title={THaLLE-ThaiLLM: Domain-Specialized Small LLMs for Finance and Thai -- Technical Report}, 
+      author={KBTG Labs and : and Anuruth Lertpiya and Danupat Khamnuansin and Kantapong Sucharitpongpan and Pornchanan Balee and Tawunrat Chalothorn and Thadpong Pongthawornkamol and Monchai Lertsutthiwong},
+      year={2026},
+      eprint={2601.04597},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2601.04597}, 
+}
+```