Instructions to use allegro/herbert-large-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allegro/herbert-large-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="allegro/herbert-large-cased")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("allegro/herbert-large-cased") model = AutoModel.from_pretrained("allegro/herbert-large-cased") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit ·
3789c08
1
Parent(s): 8d1ad1f
Change default tokenizer to HerbertTokenizerFast
Browse files- config.json +1 -1
config.json
CHANGED
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@@ -20,7 +20,7 @@
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"pooler_num_fc_layers": 3,
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"pooler_size_per_head": 128,
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"pooler_type": "first_token_transform",
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-
"tokenizer_class": "
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"type_vocab_size": 2,
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"vocab_size": 50000
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}
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"pooler_num_fc_layers": 3,
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"pooler_size_per_head": 128,
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"pooler_type": "first_token_transform",
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+
"tokenizer_class": "HerbertTokenizerFast",
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"type_vocab_size": 2,
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"vocab_size": 50000
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}
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