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# /// script
# requires-python = ">=3.12"
# dependencies = [
# "numpy",
# "einops",
# "torch",
# "transformers",
# "datasets",
# "accelerate",
# "timm",
# ]
# ///
try:
# prepare the model input
prompt = "Give me a brief explanation of gravity in simple terms."
messages_think = [
{"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
messages_think,
tokenize=False,
add_generation_prompt=True,
)
model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
# Generate the output
generated_ids = model.generate(**model_inputs, max_new_tokens=32768)
# Get and decode the output
output_ids = generated_ids[0][len(model_inputs.input_ids[0]) :]
print(tokenizer.decode(output_ids, skip_special_tokens=True))
with open('HuggingFaceTB_SmolLM3-3B_4.txt', 'w') as f:
f.write('Everything was good in HuggingFaceTB_SmolLM3-3B_4.txt')
except Exception as e:
with open('HuggingFaceTB_SmolLM3-3B_4.txt', 'w') as f:
import traceback
traceback.print_exc(file=f)
finally:
from huggingface_hub import upload_file
upload_file(
path_or_fileobj='HuggingFaceTB_SmolLM3-3B_4.txt',
repo_id='model-metadata/custom_code_execution_files',
path_in_repo='HuggingFaceTB_SmolLM3-3B_4.txt',
repo_type='dataset',
) |