Instructions to use tobiges/behavior_fast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tobiges/behavior_fast with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tobiges/behavior_fast", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload processor
Browse files- processing_action_tokenizer.py +3 -9
- tokenizer.json +0 -0
processing_action_tokenizer.py
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@@ -164,15 +164,9 @@ class UniversalActionProcessor(ProcessorMixin):
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# Train BPE tokenizer
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tokenizer = Tokenizer(BPE())
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tokenizer.pre_tokenizer = pre_tokenizers.ByteLevel(
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)
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tokenizer.decoder = decoders.ByteLevel(
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add_prefix_space=False, trim_offsets=False, use_regex=False
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)
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tokenizer.post_processor = processors.ByteLevel(
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add_prefix_space=False, trim_offsets=False, use_regex=False
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)
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trainer = BpeTrainer(
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vocab_size=vocab_size,
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# Train BPE tokenizer
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tokenizer = Tokenizer(BPE())
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tokenizer.pre_tokenizer = pre_tokenizers.ByteLevel(add_prefix_space=False, use_regex=False)
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tokenizer.decoder = decoders.ByteLevel()
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tokenizer.post_processor = processors.ByteLevel(trim_offsets=False)
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trainer = BpeTrainer(
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vocab_size=vocab_size,
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tokenizer.json
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