Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use henryscheible/bert-large-uncased_crows_pairs_finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henryscheible/bert-large-uncased_crows_pairs_finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henryscheible/bert-large-uncased_crows_pairs_finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("henryscheible/bert-large-uncased_crows_pairs_finetuned") model = AutoModelForSequenceClassification.from_pretrained("henryscheible/bert-large-uncased_crows_pairs_finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 189 Bytes
4af5ff7 | 1 2 3 4 5 6 7 | {
"heads_preserved_at_max_icat": 309,
"icat_pruned": 50.51054860980168,
"ss_pruned": 50.758399521560435,
"icat_base": 45.934908690486644,
"ss_base": 51.629449136664014
} |