| --- |
| language: |
| - km |
| tags: |
| - math-word-problems |
| - khmer |
| - qwen2.5 |
| - fine-tuned |
| base_model: Qwen/Qwen2.5-3B |
| --- |
| |
| # Khmer Math Word Problems β Qwen2.5-3B Fine-tune |
|
|
| This model solves Khmer-language math word problems step by step. |
|
|
| ## Usage |
| ```python |
| from transformers import AutoTokenizer, AutoModelForCausalLM |
| import torch |
| |
| model = AutoModelForCausalLM.from_pretrained( |
| "SORNPov/Chamnaot", |
| dtype=torch.float16, |
| device_map="auto" |
| ) |
| tokenizer = AutoTokenizer.from_pretrained("SORNPov/Chamnaot") |
| |
| question = "αααααα
αααααα
ααΈααα (your Khmer math question here)" |
| prompt = f"question: {question} guidance: " |
| |
| inputs = tokenizer(prompt, return_tensors="pt").to(model.device) |
| |
| output = model.generate( |
| **inputs, |
| max_new_tokens=800, |
| do_sample=False, |
| pad_token_id=tokenizer.eos_token_id |
| ) |
| |
| input_len = inputs["input_ids"].shape[1] |
| print(tokenizer.decode(output[0][input_len:], skip_special_tokens=True)) |
| ``` |
|
|