Text Classification
Transformers
Safetensors
English
bert
arxiv
scientific-text-classification
scibert
streamlit-demo
text-embeddings-inference
Instructions to use Ian-Khalzov/article-topic-service-scibert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ian-Khalzov/article-topic-service-scibert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ian-Khalzov/article-topic-service-scibert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ian-Khalzov/article-topic-service-scibert") model = AutoModelForSequenceClassification.from_pretrained("Ian-Khalzov/article-topic-service-scibert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 59314c1c650a5b20d8a27fbbe8c8a53e2070da33919500aedf974fbf5d1aaa55
- Size of remote file:
- 440 MB
- SHA256:
- 1bb43480cebf6a605d7ea6fc34268b5caac9fdc6b31296205b6b58bae8e579b5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.