Instructions to use amazon-sagemaker-community/encoder_decoder_es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amazon-sagemaker-community/encoder_decoder_es with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("amazon-sagemaker-community/encoder_decoder_es") model = AutoModelForSeq2SeqLM.from_pretrained("amazon-sagemaker-community/encoder_decoder_es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from amazon-sagemaker-community/encoder_decoder_es: direct link, hf CLI and curl.
- Browser
- Download file 332 Bytes
-
https://huggingface.co/amazon-sagemaker-community/encoder_decoder_es/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://amazon-sagemaker-community/encoder_decoder_es/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/amazon-sagemaker-community/encoder_decoder_es/resolve/main/tokenizer_config.json
332 Bytes
| {"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "add_prefix_space": false, "errors": "replace", "sep_token": "</s>", "cls_token": "<s>", "pad_token": "<pad>", "mask_token": "<mask>", "special_tokens_map_file": null, "name_or_path": "bertin-project/bertin-roberta-base-spanish", "tokenizer_class": "RobertaTokenizer"} |