Instructions to use liddlefish/privacyembeddingv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use liddlefish/privacyembeddingv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="liddlefish/privacyembeddingv2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("liddlefish/privacyembeddingv2") model = AutoModel.from_pretrained("liddlefish/privacyembeddingv2") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer
Browse files- tokenizer.json +1 -0
tokenizer.json
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"end_of_word_suffix": "",
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"fuse_unk": false,
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"byte_fallback": false,
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"vocab": {
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"<s>": 0,
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"<pad>": 1,
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"end_of_word_suffix": "",
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"fuse_unk": false,
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"byte_fallback": false,
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"ignore_merges": false,
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"vocab": {
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"<s>": 0,
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"<pad>": 1,
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