Instructions to use Adapting/Knowledge-Driven-Dialogue with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Adapting/Knowledge-Driven-Dialogue with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Adapting/Knowledge-Driven-Dialogue") model = AutoModelForSeq2SeqLM.from_pretrained("Adapting/Knowledge-Driven-Dialogue") - Notebooks
- Google Colab
- Kaggle
| { | |
| "cls_token": "[CLS]", | |
| "do_basic_tokenize": true, | |
| "do_lower_case": false, | |
| "mask_token": "[MASK]", | |
| "model_max_length": 128, | |
| "name_or_path": "Adapting/Knowledge-Driven-Dialogue", | |
| "never_split": null, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "special_tokens_map_file": "gpt2-base-chinese-cluecorpussmall\\special_tokens_map.json", | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "BertTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |