# /// script # requires-python = ">=3.12" # dependencies = [ # "torch", # "torchvision", # "transformers", # "diffusers", # "sentence-transformers", # "accelerate", # "peft", # "slack-sdk", # ] # /// try: from sentence_transformers import SentenceTransformer model = SentenceTransformer("Qwen/Qwen3-Embedding-0.6B") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] with open('Qwen_Qwen3-Embedding-0.6B_0.txt', 'w', encoding='utf-8') as f: f.write('Everything was good in Qwen_Qwen3-Embedding-0.6B_0.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 ', ) with open('Qwen_Qwen3-Embedding-0.6B_0.txt', 'a', encoding='utf-8') as f: import traceback f.write('''```CODE: from sentence_transformers import SentenceTransformer model = SentenceTransformer("Qwen/Qwen3-Embedding-0.6B") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] ``` ERROR: ''') traceback.print_exc(file=f) finally: from huggingface_hub import upload_file upload_file( path_or_fileobj='Qwen_Qwen3-Embedding-0.6B_0.txt', repo_id='model-metadata/code_execution_files', path_in_repo='Qwen_Qwen3-Embedding-0.6B_0.txt', repo_type='dataset', )