Instructions to use answerdotai/ModernBERT-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use answerdotai/ModernBERT-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="answerdotai/ModernBERT-large")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("answerdotai/ModernBERT-large") model = AutoModelForMaskedLM.from_pretrained("answerdotai/ModernBERT-large") - Notebooks
- Google Colab
- Kaggle
Set tokenizer "model_max_length" property to 8192 (#9)
Browse files- Set tokenizer "model_max_length" property to 8192 (63bbcb45c87362a3f38c2c4489a6ffab82181cd2)
Co-authored-by: Antoine Chaffin <NohTow@users.noreply.huggingface.co>
- tokenizer_config.json +1 -1
tokenizer_config.json
CHANGED
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@@ -932,7 +932,7 @@
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| 932 |
"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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| 934 |
"mask_token": "[MASK]",
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| 935 |
-
"model_max_length":
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| 936 |
"pad_token": "[PAD]",
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| 937 |
"sep_token": "[SEP]",
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| 938 |
"tokenizer_class": "PreTrainedTokenizerFast",
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"clean_up_tokenization_spaces": true,
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| 933 |
"cls_token": "[CLS]",
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| 934 |
"mask_token": "[MASK]",
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| 935 |
+
"model_max_length": 8192,
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| 936 |
"pad_token": "[PAD]",
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| 937 |
"sep_token": "[SEP]",
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| 938 |
"tokenizer_class": "PreTrainedTokenizerFast",
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