Instructions to use DimitriosPanagoulias/MemoryBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DimitriosPanagoulias/MemoryBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DimitriosPanagoulias/MemoryBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DimitriosPanagoulias/MemoryBERT") model = AutoModelForSequenceClassification.from_pretrained("DimitriosPanagoulias/MemoryBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f12ed9ae63e87091223d9679410955e4b90015e4aa89bf566c6ad63ec9f65ca
- Size of remote file:
- 5.39 kB
- SHA256:
- 5f6d562bc8eecf58632b0f7f99ba17ab5c0f68ac67bcff8fdbaba3d8d20350ea
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