Instructions to use Melih1234/learning_first_tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Melih1234/learning_first_tokenizer with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Melih1234/learning_first_tokenizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Melih1234/learning_first_tokenizer: direct link, hf CLI and curl.
- Browser
- Download file 376 Bytes
-
https://huggingface.co/Melih1234/learning_first_tokenizer/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Melih1234/learning_first_tokenizer/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Melih1234/learning_first_tokenizer/resolve/main/tokenizer_config.json
376 Bytes
| { | |
| "added_tokens_decoder": { | |
| "0": { | |
| "content": "<unk>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| } | |
| }, | |
| "clean_up_tokenization_spaces": false, | |
| "extra_special_tokens": {}, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "tokenizer_class": "PreTrainedTokenizerFast" | |
| } | |