Instructions to use ahnaf702/SentibertLarge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahnaf702/SentibertLarge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ahnaf702/SentibertLarge")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ahnaf702/SentibertLarge") model = AutoModelForSequenceClassification.from_pretrained("ahnaf702/SentibertLarge") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0fb6da240e62930047a2aa41a46b8244144999c83dd7e86e304699b94d5487f8
- Size of remote file:
- 235 MB
- SHA256:
- 2fbcc3ff93b0c8cd34785813c440440630ac68b882db1ff876a0b5ece9d16e46
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