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
File size: 404 Bytes
da3f3e5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"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]"
}
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