Instructions to use fangyuan/tqa_extractive_compressor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fangyuan/tqa_extractive_compressor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="fangyuan/tqa_extractive_compressor")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("fangyuan/tqa_extractive_compressor") model = AutoModel.from_pretrained("fangyuan/tqa_extractive_compressor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7667aac3ae425023fc5d6b694f5514c81f32a61b73a3a5199be746a6a4b0bc3
- Size of remote file:
- 438 MB
- SHA256:
- b70c4249ef908012c0cfb1148392d445693d6b997e9241899430efe06802ebf1
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