Feature Extraction
Transformers
Safetensors
Korean
han2han
text-generation
hanja
hangul
historical-korean
encoder-decoder
custom_code
Instructions to use cadazar/han2han-pt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cadazar/han2han-pt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="cadazar/han2han-pt", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("cadazar/han2han-pt", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from cadazar/han2han-pt: direct link, hf CLI and curl.
- Browser
- Download file 328 Bytes
-
https://huggingface.co/cadazar/han2han-pt/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://cadazar/han2han-pt/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/cadazar/han2han-pt/resolve/main/tokenizer_config.json
328 Bytes
| { | |
| "backend": "tokenizers", | |
| "bos_token": "<s>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "</s>", | |
| "mask_token": "<mask>", | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 2048, | |
| "pad_token": "<pad>", | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": "<unk>" | |
| } | |