Instructions to use memray/AugTriever-Hybrid-TQGen-plus-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use memray/AugTriever-Hybrid-TQGen-plus-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="memray/AugTriever-Hybrid-TQGen-plus-BERT")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("memray/AugTriever-Hybrid-TQGen-plus-BERT") model = AutoModel.from_pretrained("memray/AugTriever-Hybrid-TQGen-plus-BERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5319548f1053409db58614e5d5a7d092a0674df3fda70cb082d675fb245c90ba
- Size of remote file:
- 436 MB
- SHA256:
- 2ba7c19414c160d7b276f79d9391eb7a7f63afc1f84c889e923c1e132f632170
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