Instructions to use xTimeCrystal/U32k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xTimeCrystal/U32k with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("xTimeCrystal/U32k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from xTimeCrystal/U32k: direct link, hf CLI and curl.
- Browser
- Download file 402 Bytes
-
https://huggingface.co/xTimeCrystal/U32k/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://xTimeCrystal/U32k/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/xTimeCrystal/U32k/resolve/main/tokenizer_config.json
402 Bytes
| { | |
| "tokenizer_class": "PreTrainedTokenizerFast", | |
| "bos_token": "<|begin_of_text|>", | |
| "eos_token": "<|end_of_text|>", | |
| "pad_token": "<|pad|>", | |
| "unk_token": "<|unk|>", | |
| "sep_token": "<|sep|>", | |
| "mask_token": "<|mask|>", | |
| "add_bos_token": false, | |
| "add_eos_token": false, | |
| "clean_up_tokenization_spaces": false, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "padding_side": "right" | |
| } | |