Text Classification
Transformers
Safetensors
exaone4
text-generation
exaone
lora
finetune
korean
tagger
Instructions to use FloatDo/exaone-4.0-1.2b-float-right-tagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FloatDo/exaone-4.0-1.2b-float-right-tagger with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FloatDo/exaone-4.0-1.2b-float-right-tagger")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("FloatDo/exaone-4.0-1.2b-float-right-tagger") model = AutoModelForCausalLM.from_pretrained("FloatDo/exaone-4.0-1.2b-float-right-tagger") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": "[BOS]", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "[|endofturn|]", | |
| "errors": "replace", | |
| "is_local": true, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "[PAD]", | |
| "padding_side": "right", | |
| "split_special_tokens": false, | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": "[UNK]" | |
| } | |