Instructions to use Nargizi/screeve-postagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nargizi/screeve-postagger with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Nargizi/screeve-postagger")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Nargizi/screeve-postagger") model = AutoModelForTokenClassification.from_pretrained("Nargizi/screeve-postagger") - Notebooks
- Google Colab
- Kaggle
update model max length
Browse files- tokenizer_config.json +1 -1
tokenizer_config.json
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@@ -7,7 +7,7 @@
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"input_ids",
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"attention_mask"
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],
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"model_max_length":
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"pad_token": "<PAD>",
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"sep_token": "<SEP>",
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"strip_accents": null,
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"input_ids",
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"attention_mask"
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],
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"model_max_length": 200,
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"pad_token": "<PAD>",
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"sep_token": "<SEP>",
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"strip_accents": null,
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