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| | try: |
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| | from transformers import AutoModelForCausalLM |
| | model = AutoModelForCausalLM.from_pretrained("ByteDance/Ouro-1.4B", trust_remote_code=True, torch_dtype="auto") |
| | with open('ByteDance_Ouro-1.4B_1.txt', 'w', encoding='utf-8') as f: |
| | f.write('Everything was good in ByteDance_Ouro-1.4B_1.txt') |
| | except Exception as e: |
| | import os |
| | from slack_sdk import WebClient |
| | client = WebClient(token=os.environ['SLACK_TOKEN']) |
| | client.chat_postMessage( |
| | channel='#hub-model-metadata-snippets-sprint', |
| | text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/ByteDance_Ouro-1.4B_1.txt|ByteDance_Ouro-1.4B_1.txt>', |
| | ) |
| |
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| | with open('ByteDance_Ouro-1.4B_1.txt', 'a', encoding='utf-8') as f: |
| | import traceback |
| | f.write('''```CODE: |
| | # Load model directly |
| | from transformers import AutoModelForCausalLM |
| | model = AutoModelForCausalLM.from_pretrained("ByteDance/Ouro-1.4B", trust_remote_code=True, torch_dtype="auto") |
| | ``` |
| | |
| | ERROR: |
| | ''') |
| | traceback.print_exc(file=f) |
| | |
| | finally: |
| | from huggingface_hub import upload_file |
| | upload_file( |
| | path_or_fileobj='ByteDance_Ouro-1.4B_1.txt', |
| | repo_id='model-metadata/code_execution_files', |
| | path_in_repo='ByteDance_Ouro-1.4B_1.txt', |
| | repo_type='dataset', |
| | ) |
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