Upload google_embeddinggemma-300m_10.py with huggingface_hub

google_embeddinggemma-300m_10.py

@@ -0,0 +1,57 @@
+# /// script
+# requires-python = ">=3.12"
+# dependencies = [
+#     "torch",
+#     "torchvision",
+#     "transformers",
+#     "accelerate",
+#     "peft",
+#     "slack-sdk",
+# ]
+# ///
+
+try:
+    model = SentenceTransformer(model_id, truncate_dim=256, similarity_fn_name="dot").to(device=device)
+    embeddings = model.encode(words, prompt_name="STS", normalize_embeddings=True)
+    
+    for idx, embedding in enumerate(embeddings):
+        print(f"Embedding {idx+1}: {embedding.shape}")
+    
+    print("-"*80)
+    check_word_similarities()
+    with open('google_embeddinggemma-300m_10.txt', 'w', encoding='utf-8') as f:
+        f.write('Everything was good in google_embeddinggemma-300m_10.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/google_embeddinggemma-300m_10.txt|google_embeddinggemma-300m_10.txt>',
+    )
+
+    with open('google_embeddinggemma-300m_10.txt', 'a', encoding='utf-8') as f:
+        import traceback
+        f.write('''```CODE: 
+model = SentenceTransformer(model_id, truncate_dim=256, similarity_fn_name="dot").to(device=device)
+embeddings = model.encode(words, prompt_name="STS", normalize_embeddings=True)
+
+for idx, embedding in enumerate(embeddings):
+    print(f"Embedding {idx+1}: {embedding.shape}")
+
+print("-"*80)
+check_word_similarities()
+```
+
+ERROR: 
+''')
+        traceback.print_exc(file=f)
+    
+finally:
+    from huggingface_hub import upload_file
+    upload_file(
+        path_or_fileobj='google_embeddinggemma-300m_10.txt',
+        repo_id='model-metadata/code_execution_files',
+        path_in_repo='google_embeddinggemma-300m_10.txt',
+        repo_type='dataset',
+    )