Instructions to use Tanor/BERTicSENTPOS4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tanor/BERTicSENTPOS4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tanor/BERTicSENTPOS4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tanor/BERTicSENTPOS4") model = AutoModelForSequenceClassification.from_pretrained("Tanor/BERTicSENTPOS4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e763ff2681a4f74208a529b4a921ee9ac1e328da3e188d434fd15bd5ac1af2d8
- Size of remote file:
- 4.98 kB
- SHA256:
- c02799e12fc6031436c7629e5081a95cbc027576ef61b1dc64e6a6bee16cf0a9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.