Text Classification
Transformers
PyTorch
English
bert
chemistry
biology
medical
text-embeddings-inference
Instructions to use terran-ai/WOS46985Bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use terran-ai/WOS46985Bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="terran-ai/WOS46985Bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("terran-ai/WOS46985Bert") model = AutoModelForSequenceClassification.from_pretrained("terran-ai/WOS46985Bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d62373fbadab12c9357f8434ae34523f665f01fff03bf1e73dab885e1e7328f
- Size of remote file:
- 438 MB
- SHA256:
- 9a58534eb0adb92ac9e8b80b5ae7ee1de340aba685fadfaccb2701b3a1d6eb79
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.