Transformers
PyTorch
English
Chinese
bart
text2text-generation
GENIUS
conditional text generation
sketch-based text generation
data augmentation
Instructions to use beyond/genius-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beyond/genius-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("beyond/genius-base") model = AutoModelForSeq2SeqLM.from_pretrained("beyond/genius-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from beyond/genius-base: direct link, hf CLI and curl.
- Browser
- Download file 434 Bytes
-
https://huggingface.co/beyond/genius-base/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://beyond/genius-base/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/beyond/genius-base/resolve/main/tokenizer_config.json
434 Bytes
| {"errors": "replace", "bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": "<mask>", "add_prefix_space": false, "trim_offsets": true, "model_max_length": 1024, "name_or_path": "../saved_models/bart-base-c4-realnewslike-4templates-passage-max15sents_2-sketch4/checkpoint-129375", "special_tokens_map_file": null, "tokenizer_class": "BartTokenizer"} |