Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use SIRIS-Lab/specter2-wos-multiclass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SIRIS-Lab/specter2-wos-multiclass with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SIRIS-Lab/specter2-wos-multiclass")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SIRIS-Lab/specter2-wos-multiclass") model = AutoModelForSequenceClassification.from_pretrained("SIRIS-Lab/specter2-wos-multiclass", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c7ca31a8701890c660963751aeefa61b195cc51ca6cac72cde133cff6d9f3f4
- Size of remote file:
- 440 MB
- SHA256:
- a69a73a9b9ffa8fa0b92ebfd50455ba14efbdee5fcc8043a2c526b96aa1e9eca
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