Instructions to use helboukkouri/character-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use helboukkouri/character-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="helboukkouri/character-bert", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("helboukkouri/character-bert", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add model files directly in the repo (#1)
- Add configuration file (b15fe97e713b597570e8c6be079f61188402dfb5) - Add modeling file (3abe3f21189d0f294823037889ead3a38a97f9f7) - Create tokenization_character_bert.py (71d6a416cf366f5f86b4eeb23eb3256476860d14) - Update config.json (670c2a06f91ebaff393d4d0fbb866789f731c6c4) - fix - make json valid (1843e3958820bd1bfc683ff0b7bd34a63ec09f93) - Update tokenizer_config.json (321f97ebd2963fc59d0ea05c8e69da7be88eca57) - Update configuration_character_bert.py (f54b4001048f6b8778ab51481cc6cfc348ce73cb) - fix import (c6807ce57bb4053b88b5a4d60cb3f07c0e4bf6c1) - fix tokenization imports (13800a431886cd0db40c909e679db9351e5287aa) - Update tokenizer_config.json (dc9bb0f39a52315d8a47762b9884b583de0d72e1) - Update config.json (77e6f7ba3360c5cd4fa5f73d47014ab857b0abbd) - Update tokenization_character_bert.py (c260e5f2ad65649b168758e86255e0d9dc51deb2) - Update tokenizer_config.json (c9c78eb252fce7b5e8bb3747646fa6cffea52323) - Update tokenizer_config.json (c3b663e0ceb23d9e72229748f02d20b7a2105317) - …b8a56ad
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Add Masked Language Modeling vocabulary
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Update CharacterBERT checkpoint with pre-training weights
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Add Tokenizer config & Update model config
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Add pretrained weights
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Remove trailing comma in json file
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Update config.json: remove unused param
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Update config.json: remove unused params
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Add config.json
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initial commit
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