Instructions to use SparkBeyond/roberta-large-sts-b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SparkBeyond/roberta-large-sts-b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SparkBeyond/roberta-large-sts-b")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SparkBeyond/roberta-large-sts-b") model = AutoModelForSequenceClassification.from_pretrained("SparkBeyond/roberta-large-sts-b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
upload flax model
19d25d2 -
allow flax
7677dc9
-
Migrate model card from transformers-repo
Read announcement at https://discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755 Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/SparkBeyond/roberta-large-sts-b/README.md0ac6ddb
-
Update config.json
54ee5fa
-
Update README.md
2791aea -
Update special_tokens_map.json
32422b3 -
Update merges.txt
66a90ec -
Update tokenizer_config.json
c691098 -
Update vocab.json
8ec5c53 -
Update config.json
59b145b -
Update pytorch_model.bin
2d9fcf0 -
initial commit
1fab108