model-metadata/model_vram_code · Datasets at Hugging Face

deepseek-ai/DeepSeek-OCR

8.08

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # ⚠️ Type of model/library unknown.\n \n # Feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('deepseek-ai_DeepSeek-OCR_0.txt', 'w') as f:\n f.write('Everything was good in deepseek-ai_DeepSeek-OCR_0.txt')\nexcept Exception as e:\n with open('deepseek-ai_DeepSeek-OCR_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='deepseek-ai_DeepSeek-OCR_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='deepseek-ai_DeepSeek-OCR_0.txt',\n repo_type='dataset',\n )" ]

[ "DO NOT EXECUTE" ]

[ "WAS NOT EXECUTED" ]

PaddlePaddle/PaddleOCR-VL

2.32

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # See https://www.paddleocr.ai/latest/version3.x/pipeline_usage/PaddleOCR-VL.html to installation\n \n from paddleocr import PaddleOCRVL\n pipeline = PaddleOCRVL()\n output = pipeline.predict(\"path/to/document_image.png\")\n for res in output:\n \tres.print()\n \tres.save_to_json(save_path=\"output\")\n \tres.save_to_markdown(save_path=\"output\")\n with open('PaddlePaddle_PaddleOCR-VL_0.txt', 'w') as f:\n f.write('Everything was good in PaddlePaddle_PaddleOCR-VL_0.txt')\nexcept Exception as e:\n with open('PaddlePaddle_PaddleOCR-VL_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='PaddlePaddle_PaddleOCR-VL_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='PaddlePaddle_PaddleOCR-VL_0.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/PaddlePaddle_PaddleOCR-VL_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/PaddlePaddle_PaddleOCR-VL_0.txt" ]

nvidia/omnivinci

0

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"feature-extraction\", model=\"nvidia/omnivinci\", trust_remote_code=True)\n with open('nvidia_omnivinci_0.txt', 'w') as f:\n f.write('Everything was good in nvidia_omnivinci_0.txt')\nexcept Exception as e:\n with open('nvidia_omnivinci_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='nvidia_omnivinci_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='nvidia_omnivinci_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModel\n model = AutoModel.from_pretrained(\"nvidia/omnivinci\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('nvidia_omnivinci_1.txt', 'w') as f:\n f.write('Everything was good in nvidia_omnivinci_1.txt')\nexcept Exception as e:\n with open('nvidia_omnivinci_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='nvidia_omnivinci_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='nvidia_omnivinci_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/nvidia_omnivinci_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/nvidia_omnivinci_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/nvidia_omnivinci_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/nvidia_omnivinci_1.txt" ]

rednote-hilab/dots.ocr

7.36

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # integration status unknown.\n \n # Please clone model and use locally.\n \n # Also feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('rednote-hilab_dots.ocr_0.txt', 'w') as f:\n f.write('Everything was good in rednote-hilab_dots.ocr_0.txt')\nexcept Exception as e:\n with open('rednote-hilab_dots.ocr_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='rednote-hilab_dots.ocr_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='rednote-hilab_dots.ocr_0.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/rednote-hilab_dots.ocr_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/rednote-hilab_dots.ocr_0.txt" ]

facebook/MobileLLM-Pro

2.63

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"facebook/MobileLLM-Pro\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('facebook_MobileLLM-Pro_0.txt', 'w') as f:\n f.write('Everything was good in facebook_MobileLLM-Pro_0.txt')\nexcept Exception as e:\n with open('facebook_MobileLLM-Pro_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='facebook_MobileLLM-Pro_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='facebook_MobileLLM-Pro_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoTokenizer, AutoModelForCausalLM\n \n tokenizer = AutoTokenizer.from_pretrained(\"facebook/MobileLLM-Pro\", trust_remote_code=True)\n model = AutoModelForCausalLM.from_pretrained(\"facebook/MobileLLM-Pro\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n inputs = tokenizer.apply_chat_template(\n \tmessages,\n \tadd_generation_prompt=True,\n \ttokenize=True,\n \treturn_dict=True,\n \treturn_tensors=\"pt\",\n ).to(model.device)\n \n outputs = model.generate(**inputs, max_new_tokens=40)\n print(tokenizer.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n with open('facebook_MobileLLM-Pro_1.txt', 'w') as f:\n f.write('Everything was good in facebook_MobileLLM-Pro_1.txt')\nexcept Exception as e:\n with open('facebook_MobileLLM-Pro_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='facebook_MobileLLM-Pro_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='facebook_MobileLLM-Pro_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/facebook_MobileLLM-Pro_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/facebook_MobileLLM-Pro_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/facebook_MobileLLM-Pro_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/facebook_MobileLLM-Pro_1.txt" ]

inclusionAI/Ling-1T

2,420.73

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"inclusionAI/Ling-1T\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('inclusionAI_Ling-1T_0.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ling-1T_0.txt')\nexcept Exception as e:\n with open('inclusionAI_Ling-1T_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ling-1T_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ling-1T_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"inclusionAI/Ling-1T\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('inclusionAI_Ling-1T_1.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ling-1T_1.txt')\nexcept Exception as e:\n with open('inclusionAI_Ling-1T_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ling-1T_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ling-1T_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_Ling-1T_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_Ling-1T_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_Ling-1T_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_Ling-1T_1.txt" ]

Open-Bee/Bee-8B-RL

21.01

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"image-text-to-text\", model=\"Open-Bee/Bee-8B-RL\", trust_remote_code=True)\n messages = [\n {\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"image\", \"url\": \"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG\"},\n {\"type\": \"text\", \"text\": \"What animal is on the candy?\"}\n ]\n },\n ]\n pipe(text=messages)\n with open('Open-Bee_Bee-8B-RL_0.txt', 'w') as f:\n f.write('Everything was good in Open-Bee_Bee-8B-RL_0.txt')\nexcept Exception as e:\n with open('Open-Bee_Bee-8B-RL_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Open-Bee_Bee-8B-RL_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='Open-Bee_Bee-8B-RL_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModel\n model = AutoModel.from_pretrained(\"Open-Bee/Bee-8B-RL\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('Open-Bee_Bee-8B-RL_1.txt', 'w') as f:\n f.write('Everything was good in Open-Bee_Bee-8B-RL_1.txt')\nexcept Exception as e:\n with open('Open-Bee_Bee-8B-RL_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Open-Bee_Bee-8B-RL_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='Open-Bee_Bee-8B-RL_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/Open-Bee_Bee-8B-RL_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/Open-Bee_Bee-8B-RL_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/Open-Bee_Bee-8B-RL_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/Open-Bee_Bee-8B-RL_1.txt" ]

inclusionAI/Ring-1T

4,841.45

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"inclusionAI/Ring-1T\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('inclusionAI_Ring-1T_0.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ring-1T_0.txt')\nexcept Exception as e:\n with open('inclusionAI_Ring-1T_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ring-1T_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ring-1T_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"inclusionAI/Ring-1T\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('inclusionAI_Ring-1T_1.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ring-1T_1.txt')\nexcept Exception as e:\n with open('inclusionAI_Ring-1T_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ring-1T_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ring-1T_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_Ring-1T_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_Ring-1T_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_Ring-1T_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_Ring-1T_1.txt" ]

nvidia/llama-embed-nemotron-8b

18.17

[]

inclusionAI/LLaDA2.0-mini-preview

39.36

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"inclusionAI/LLaDA2.0-mini-preview\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('inclusionAI_LLaDA2.0-mini-preview_0.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_LLaDA2.0-mini-preview_0.txt')\nexcept Exception as e:\n with open('inclusionAI_LLaDA2.0-mini-preview_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_LLaDA2.0-mini-preview_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_LLaDA2.0-mini-preview_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"inclusionAI/LLaDA2.0-mini-preview\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('inclusionAI_LLaDA2.0-mini-preview_1.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_LLaDA2.0-mini-preview_1.txt')\nexcept Exception as e:\n with open('inclusionAI_LLaDA2.0-mini-preview_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_LLaDA2.0-mini-preview_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_LLaDA2.0-mini-preview_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_LLaDA2.0-mini-preview_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_LLaDA2.0-mini-preview_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_LLaDA2.0-mini-preview_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_LLaDA2.0-mini-preview_1.txt" ]

inclusionAI/LLaDA2.0-flash-preview

249.14

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"inclusionAI/LLaDA2.0-flash-preview\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('inclusionAI_LLaDA2.0-flash-preview_0.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_LLaDA2.0-flash-preview_0.txt')\nexcept Exception as e:\n with open('inclusionAI_LLaDA2.0-flash-preview_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_LLaDA2.0-flash-preview_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_LLaDA2.0-flash-preview_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"inclusionAI/LLaDA2.0-flash-preview\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('inclusionAI_LLaDA2.0-flash-preview_1.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_LLaDA2.0-flash-preview_1.txt')\nexcept Exception as e:\n with open('inclusionAI_LLaDA2.0-flash-preview_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_LLaDA2.0-flash-preview_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_LLaDA2.0-flash-preview_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_LLaDA2.0-flash-preview_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_LLaDA2.0-flash-preview_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_LLaDA2.0-flash-preview_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_LLaDA2.0-flash-preview_1.txt" ]

inclusionAI/Ring-mini-sparse-2.0-exp

78.72

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"inclusionAI/Ring-mini-sparse-2.0-exp\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('inclusionAI_Ring-mini-sparse-2.0-exp_0.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ring-mini-sparse-2.0-exp_0.txt')\nexcept Exception as e:\n with open('inclusionAI_Ring-mini-sparse-2.0-exp_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ring-mini-sparse-2.0-exp_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ring-mini-sparse-2.0-exp_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"inclusionAI/Ring-mini-sparse-2.0-exp\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('inclusionAI_Ring-mini-sparse-2.0-exp_1.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ring-mini-sparse-2.0-exp_1.txt')\nexcept Exception as e:\n with open('inclusionAI_Ring-mini-sparse-2.0-exp_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ring-mini-sparse-2.0-exp_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ring-mini-sparse-2.0-exp_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_Ring-mini-sparse-2.0-exp_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_Ring-mini-sparse-2.0-exp_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_Ring-mini-sparse-2.0-exp_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_Ring-mini-sparse-2.0-exp_1.txt" ]

inclusionAI/Ring-flash-linear-2.0-128k

504.54

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"inclusionAI/Ring-flash-linear-2.0-128k\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('inclusionAI_Ring-flash-linear-2.0-128k_0.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ring-flash-linear-2.0-128k_0.txt')\nexcept Exception as e:\n with open('inclusionAI_Ring-flash-linear-2.0-128k_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ring-flash-linear-2.0-128k_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ring-flash-linear-2.0-128k_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"inclusionAI/Ring-flash-linear-2.0-128k\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('inclusionAI_Ring-flash-linear-2.0-128k_1.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ring-flash-linear-2.0-128k_1.txt')\nexcept Exception as e:\n with open('inclusionAI_Ring-flash-linear-2.0-128k_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ring-flash-linear-2.0-128k_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ring-flash-linear-2.0-128k_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_Ring-flash-linear-2.0-128k_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_Ring-flash-linear-2.0-128k_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_Ring-flash-linear-2.0-128k_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_Ring-flash-linear-2.0-128k_1.txt" ]

moonshotai/Kimi-K2-Instruct-0905

4,971.07

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"moonshotai/Kimi-K2-Instruct-0905\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('moonshotai_Kimi-K2-Instruct-0905_0.txt', 'w') as f:\n f.write('Everything was good in moonshotai_Kimi-K2-Instruct-0905_0.txt')\nexcept Exception as e:\n with open('moonshotai_Kimi-K2-Instruct-0905_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='moonshotai_Kimi-K2-Instruct-0905_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='moonshotai_Kimi-K2-Instruct-0905_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"moonshotai/Kimi-K2-Instruct-0905\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('moonshotai_Kimi-K2-Instruct-0905_1.txt', 'w') as f:\n f.write('Everything was good in moonshotai_Kimi-K2-Instruct-0905_1.txt')\nexcept Exception as e:\n with open('moonshotai_Kimi-K2-Instruct-0905_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='moonshotai_Kimi-K2-Instruct-0905_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='moonshotai_Kimi-K2-Instruct-0905_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/moonshotai_Kimi-K2-Instruct-0905_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/moonshotai_Kimi-K2-Instruct-0905_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/moonshotai_Kimi-K2-Instruct-0905_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/moonshotai_Kimi-K2-Instruct-0905_1.txt" ]

tencent/HunyuanImage-3.0

201

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"tencent/HunyuanImage-3.0\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('tencent_HunyuanImage-3.0_0.txt', 'w') as f:\n f.write('Everything was good in tencent_HunyuanImage-3.0_0.txt')\nexcept Exception as e:\n with open('tencent_HunyuanImage-3.0_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='tencent_HunyuanImage-3.0_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='tencent_HunyuanImage-3.0_0.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/tencent_HunyuanImage-3.0_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/tencent_HunyuanImage-3.0_0.txt" ]

deepseek-ai/DeepSeek-R1

1,657.55

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"deepseek-ai/DeepSeek-R1\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('deepseek-ai_DeepSeek-R1_0.txt', 'w') as f:\n f.write('Everything was good in deepseek-ai_DeepSeek-R1_0.txt')\nexcept Exception as e:\n with open('deepseek-ai_DeepSeek-R1_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='deepseek-ai_DeepSeek-R1_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='deepseek-ai_DeepSeek-R1_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoTokenizer, AutoModelForCausalLM\n \n tokenizer = AutoTokenizer.from_pretrained(\"deepseek-ai/DeepSeek-R1\", trust_remote_code=True)\n model = AutoModelForCausalLM.from_pretrained(\"deepseek-ai/DeepSeek-R1\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n inputs = tokenizer.apply_chat_template(\n \tmessages,\n \tadd_generation_prompt=True,\n \ttokenize=True,\n \treturn_dict=True,\n \treturn_tensors=\"pt\",\n ).to(model.device)\n \n outputs = model.generate(**inputs, max_new_tokens=40)\n print(tokenizer.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n with open('deepseek-ai_DeepSeek-R1_1.txt', 'w') as f:\n f.write('Everything was good in deepseek-ai_DeepSeek-R1_1.txt')\nexcept Exception as e:\n with open('deepseek-ai_DeepSeek-R1_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='deepseek-ai_DeepSeek-R1_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='deepseek-ai_DeepSeek-R1_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/deepseek-ai_DeepSeek-R1_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/deepseek-ai_DeepSeek-R1_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/deepseek-ai_DeepSeek-R1_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/deepseek-ai_DeepSeek-R1_1.txt" ]