Text Classification
Transformers
Safetensors
bert
research-library
repository-library
metadata-category-classifier
m2
t1_metadata
v2
text-embeddings-inference
Instructions to use PeytonT/research-library-m2-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PeytonT/research-library-m2-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PeytonT/research-library-m2-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PeytonT/research-library-m2-v2") model = AutoModelForSequenceClassification.from_pretrained("PeytonT/research-library-m2-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!