Instructions to use samagra14wefi/PreferED with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use samagra14wefi/PreferED with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://samagra14wefi/PreferED") - Notebooks
- Google Colab
- Kaggle
| { | |
| "bos_token": "[CLS]", | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "[CLS]", | |
| "do_lower_case": false, | |
| "eos_token": "[SEP]", | |
| "mask_token": "[MASK]", | |
| "max_length": 512, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "sp_model_kwargs": {}, | |
| "split_by_punct": false, | |
| "stride": 0, | |
| "tokenizer_class": "DebertaV2Tokenizer", | |
| "truncation_side": "right", | |
| "truncation_strategy": "longest_first", | |
| "unk_token": "[UNK]", | |
| "vocab_type": "spm" | |
| } | |