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# /// script
# requires-python = ">=3.12"
# dependencies = [
# "torch",
# "torchvision",
# "transformers",
# "accelerate",
# "peft",
# "slack-sdk",
# ]
# ///
try:
# Load model directly
from transformers import AutoProcessor, AutoModelForVision2Seq
processor = AutoProcessor.from_pretrained("datalab-to/chandra")
model = AutoModelForVision2Seq.from_pretrained("datalab-to/chandra")
with open('datalab-to_chandra_1.txt', 'w', encoding='utf-8') as f:
f.write('Everything was good in datalab-to_chandra_1.txt')
except Exception as e:
import os
from slack_sdk import WebClient
client = WebClient(token=os.environ['SLACK_TOKEN'])
client.chat_postMessage(
channel='#exp-slack-alerts',
text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/datalab-to_chandra_1.txt|datalab-to_chandra_1.txt>',
)
with open('datalab-to_chandra_1.txt', 'a', encoding='utf-8') as f:
import traceback
f.write('```CODE:
# Load model directly
from transformers import AutoProcessor, AutoModelForVision2Seq
processor = AutoProcessor.from_pretrained("datalab-to/chandra")
model = AutoModelForVision2Seq.from_pretrained("datalab-to/chandra")
```
ERROR:
')
traceback.print_exc(file=f)
finally:
from huggingface_hub import upload_file
upload_file(
path_or_fileobj='datalab-to_chandra_1.txt',
repo_id='model-metadata/code_execution_files',
path_in_repo='datalab-to_chandra_1.txt',
repo_type='dataset',
)
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