| ========== ORIGINAL PROMPT ========== |
| def build_open_ended_prompt(sample):
|
| """Build an open-ended prompt (no MCQ options)."""
|
| desc = sample.get('description', '')
|
| question = sample.get('question', '')
|
|
|
| prompt = f"""Look at the image and answer the physics question.
|
|
|
| {desc}
|
|
|
| {question}
|
|
|
|
|
| ========== ORIGINAL GENERATE ========== |
| output_ids = model.generate(**inputs, max_new_tokens=MAX_NEW_TOKENS)
|
|
|
| generated = output_ids[0][inputs.input_ids.shape[1]:]
|
| response = processor.decode(generated, skip_special_tokens=True)
|
| except Exception as e:
|
| response = f"ERROR: {str(e)}"
|
|
|
| ========== MY PROMPT ========== |
| def build_open_ended_prompt(sample): |
| q = sample.get("question", "") |
| return f"Look at this image and answer the physics question. Think step by step and put your final answer in \\boxed{{}}.\n\nQuestion: {q}" |
|
|
| def run_inference_on_gpu(gpu_id, model_path, samples, output_file): |
| """Run inference for a subset of samples on a specific GPU.""" |
|
|
| ========== MY GENERATE ========== |
| output_ids = model.generate(**inputs, max_new_tokens=2048, temperature=0.1, do_sample=False) |
| |
| output_text = processor.batch_decode(output_ids[:, inputs.input_ids.shape[1]:], |
| skip_special_tokens=True)[0] |
|
|
