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:
- 14b266c0d5495077fa3763d134779cfe3c71d58182070af3443d24744586490d
- Size of remote file:
- 2.99 kB
- SHA256:
- 62a1972d91d1db0418ecb1f8e0691367abda93645b6779257d30f080b41a8852
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