Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use jsudol/scibert-acm-multilabel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jsudol/scibert-acm-multilabel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jsudol/scibert-acm-multilabel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jsudol/scibert-acm-multilabel") model = AutoModelForSequenceClassification.from_pretrained("jsudol/scibert-acm-multilabel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 50784d6d7b39253209131d939896ba32692639cfb98f99515125c9d0c74a4407
- Size of remote file:
- 5.27 kB
- SHA256:
- 9aad58e6fe4ab70e32feaf167527a6b05e11f32984a4296a3d2697f8156acea8
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