Instructions to use sasi2400/IntangibleBERT2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sasi2400/IntangibleBERT2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sasi2400/IntangibleBERT2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sasi2400/IntangibleBERT2") model = AutoModelForSequenceClassification.from_pretrained("sasi2400/IntangibleBERT2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76f710fb0731e1440adb4e422f955df63aa28cc83bfd7ddfc9540442c6253b34
- Size of remote file:
- 4.09 kB
- SHA256:
- 731c23b420404bbbc750b1c1d15c3cd0af74c0126bd9ba3a07cbbbe2d9144152
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