Text Classification
Transformers
Safetensors
multilingual
xlm-roberta
cross-encoder
reranker
feed-ranking
enterprise-feed
learning-to-rank
text-embeddings-inference
Instructions to use FDS-Iterations/third-pass-feed-ranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FDS-Iterations/third-pass-feed-ranker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FDS-Iterations/third-pass-feed-ranker")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FDS-Iterations/third-pass-feed-ranker") model = AutoModelForSequenceClassification.from_pretrained("FDS-Iterations/third-pass-feed-ranker", device_map="auto") - Notebooks
- Google Colab
- Kaggle