Instructions to use HiTZ/JaunBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HiTZ/JaunBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HiTZ/JaunBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("HiTZ/JaunBERT") model = AutoModelForMaskedLM.from_pretrained("HiTZ/JaunBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 601 Bytes
e0ba726 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | {
"add_prefix_space": true,
"backend": "tokenizers",
"bos_token": "<s>",
"clean_up_tokenization_spaces": false,
"eos_token": "</s>",
"extra_special_tokens": [
"<mask>"
],
"is_local": true,
"legacy": true,
"local_files_only": false,
"mask_token": "<mask>",
"model_input_names": [
"input_ids",
"attention_mask"
],
"model_max_length": 8192,
"pad_token": "<pad>",
"padding_side": "right",
"sp_model_kwargs": {},
"spaces_between_special_tokens": false,
"tokenizer_class": "TokenizersBackend",
"unk_token": "<unk>",
"use_default_system_prompt": false
}
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