camel/datahubs/clients/huggingface.py Outdated Comment on lines 258 to 262 if not existing_records: raise ValueError( f"Dataset '{dataset_name}' does not have an existing file to " f"update. Use `add_records` first." ) Member Wendong-Fan Dec 8, 2024 add records directly and...
hugging-face-image-ocr-dataset-upload-example https://huggingface.co/datasets/developer0hye/korocr Refer to the official documentation to ensure you don't spend more than 12 hours uploading your dataset to Hugging Face Datasets. Familiarize yourself with the code and dataset directory structure. dat...
This should solve issue #1311. I re-uploaded the dataset to parquet format here: https://huggingface.co/datasets/mteb/mlsum as suggested by @lhoestq, to avoid using the script generation for loading.
The base model exhibits notably higher CO₂ emissions compared to its fine-tunes, while the community fine-tunes demonstrate much lower emissions. 96 + 97 + ### Model Comparison 98 + We can compare these three models using our [Comparator tool](https://huggingface.co/spaces/open-llm-...
执行完以上步骤后 dataset 目录便是预处理完成的数据,可以删除dataset_raw文件夹了 ## 训练 ```shell python train.py -c configs/config.json -m 44k ``` 注:训练时会自动清除老的模型,只保留最新3个模型,如果想防止过拟合需要自己手动备份模型记录点,或修改配置文件keep_ckpts 0为永不清除 ## 推理 使用...
If a folder is being uploaded that has over 100 files, or is onto a dataset, put a message/warning reading something alikeWARNING: upload_folder cannot be restarted without losing progress and has a single worker by default. Only use this for small amounts of data., actual message can be...
"https://huggingface.co/datasets/nvidia/ChatRAG-Bench/viewer/doqa_cooking" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "name = \"doqa_cooking\"\n", "df = load_dataset(\"nvidia/ChatRAG-Bench\", name)[\"test\"].to_...
metadata={"help": "Which type of datasets to evaluate on. default is test, must be one of (test, valid, dev)"} ) eval_dataset_fp_conf_path: str = field( default = root_dir + os.path.sep + 'conf' + os.path.sep + 'dataset_fp.json', metadata={"help": "Path of dataset_n...
" transforms.ToTensor(), # Convert images to tensor\n", "])\n", "\n", "# Create the dataset\n", "image_dataset = ImageDataset(urls=good_urls, transform=transform)\n", "image_data_loader = DataLoader(image_dataset, batch_size=4, num_workers=2, pin_memory=True)\n", "\n", "...
执行完以上步骤后 dataset 目录便是预处理完成的数据,可以删除dataset_raw文件夹了 --- ## 训练 ```shell python train.py -c configs/config.json -m 32k ``` --- ## 推理 使用[inference_main.py](inference_main.py) 使用 [inference_main.py](inference_main.py) + 更改model_path为你自己训练的...