Fill-Mask
Transformers
Safetensors
Luxembourgish
modernbert
encoder
luxembourgish
multilingual
masked-language-modeling
Instructions to use instilux/ltz-e1-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use instilux/ltz-e1-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="instilux/ltz-e1-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("instilux/ltz-e1-base") model = AutoModelForMaskedLM.from_pretrained("instilux/ltz-e1-base") - Notebooks
- Google Colab
- Kaggle
File size: 1,328 Bytes
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"add_bos_token": true,
"add_eos_token": false,
"add_prefix_space": false,
"added_tokens_decoder": {
"0": {
"content": "[CLS]",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"1": {
"content": "[SEP]",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"2": {
"content": "[PAD]",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"3": {
"content": "[MASK]",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"4": {
"content": "[UNK]",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
}
},
"bos_token": "[CLS]",
"clean_up_tokenization_spaces": true,
"cls_token": "[CLS]",
"eos_token": "[SEP]",
"extra_special_tokens": {},
"mask_token": "[MASK]",
"model_input_names": [
"input_ids",
"attention_mask"
],
"model_max_length": 1024,
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"tokenizer_class": "GPTNeoXTokenizer",
"unk_token": "[UNK]"
}
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