Instructions to use melll-uff/itd_longformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use melll-uff/itd_longformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="melll-uff/itd_longformer")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("melll-uff/itd_longformer") model = AutoModelForMaskedLM.from_pretrained("melll-uff/itd_longformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from melll-uff/itd_longformer: direct link, hf CLI and curl.
- Browser
- Download file 112 Bytes
-
https://huggingface.co/melll-uff/itd_longformer/resolve/7424928f372f99a39a61f4a28f036e9d8a4752ac/special_tokens_map.json
- Command line
-
hf download hf://melll-uff/itd_longformer@7424928f372f99a39a61f4a28f036e9d8a4752ac/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/melll-uff/itd_longformer/resolve/7424928f372f99a39a61f4a28f036e9d8a4752ac/special_tokens_map.json
112 Bytes
| {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"} |