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# /// script
# requires-python = ">=3.12"
# dependencies = [
# "numpy",
# "einops",
# "torch",
# "transformers",
# "datasets",
# "accelerate",
# "timm",
# ]
# ///
try:
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "HuggingFaceTB/SmolLM3-3B"
device = "cuda" # for GPU usage or "cpu" for CPU usage
# load the tokenizer and the model
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
model_name,
).to(device)
with open('HuggingFaceTB_SmolLM3-3B_3.txt', 'w') as f:
f.write('Everything was good in HuggingFaceTB_SmolLM3-3B_3.txt')
except Exception as e:
with open('HuggingFaceTB_SmolLM3-3B_3.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_3.txt',
repo_id='model-metadata/custom_code_execution_files',
path_in_repo='HuggingFaceTB_SmolLM3-3B_3.txt',
repo_type='dataset',
) |