auan-llm-928m-base-preview

Model Details

• Architecture: Qwen2ForCausalLM
• Parameters: ~928M
• Initialization: random initialization, trained from scratch
• Vocabulary: 32,000-token Thai byte-level BPE tokenizer
• Context length: 2,048 tokens
• Hidden size: 2,048
• Layers: 18
• Attention heads: 16
• KV heads: 4
• Intermediate size: 5,504

Training Snapshot

• Checkpoint: best validation checkpoint
• Step: 5,500
• Validation loss: 2.51767520904541
• Training objective: next-token prediction
• Precision during training: bf16

Training Data

The training configuration included Thai-focused corpora such as:

• SPAISS6F1/slm-pretrain-corpus
• SPAISS6F1/Finance
• pythainlp/thai-wiki-dataset-v3
• pythainlp/thailaw-v1.0
• pythainlp/thai-constitution-corpus
• pythainlp/thai-financial-dataset

Please audit dataset licenses and suitability before commercial use.

Usage

python
Copy code
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "YOUR_USERNAME/thai-llm-928m-base-preview"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, dtype=torch.float16)
model.eval()

prompt = "ประเทศไทยมี"
inputs = tokenizer(prompt, return_tensors="pt")

with torch.no_grad():
    output = model.generate(
        **inputs,
        max_new_tokens=80,
        do_sample=True,
        temperature=0.8,
        top_p=0.95,
        repetition_penalty=1.1,
        pad_token_id=tokenizer.eos_token_id,
    )

print(tokenizer.decode(output[0], skip_special_tokens=True))

Limitations

• This is an early base checkpoint, not a chat assistant.
• Generation quality may be unstable or repetitive.
• The model has not been aligned for safety.
• The model may hallucinate or produce inappropriate text.
• It should not be used for high-stakes decisions without further evaluation and alignment.