Instructions to use kwang2049/TSDAE-cqadupstack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kwang2049/TSDAE-cqadupstack with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="kwang2049/TSDAE-cqadupstack")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kwang2049/TSDAE-cqadupstack") model = AutoModel.from_pretrained("kwang2049/TSDAE-cqadupstack", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer_config.json
Browse files- tokenizer_config.json +1 -0
tokenizer_config.json
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{"do_lower_case": true, "model_max_length": 512, "special_tokens_map_file": "seed5/tsdae-did-all-cls/mdir_final/special_tokens_map.json", "full_tokenizer_file": null}
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