Instructions to use nkasmanoff/tool-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nkasmanoff/tool-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nkasmanoff/tool-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nkasmanoff/tool-bert") model = AutoModelForSequenceClassification.from_pretrained("nkasmanoff/tool-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 79fc39e3d4f14ed778fb5cfefa831b2ac95c4126cdbe92c7d4d793f716f1e498
- Size of remote file:
- 5.05 kB
- SHA256:
- 4caa93fffa53fd64ebdf6c5724a7f4c15dc5a635ad77f5a77997944eaf19bf6f
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