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# /// 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='#hub-model-metadata-snippets-sprint',
text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Qwen_Qwen3-Embedding-0.6B_0.txt|Qwen_Qwen3-Embedding-0.6B_0.txt>',
)
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',
)
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