Instructions to use jparmet/pusa-topic-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jparmet/pusa-topic-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jparmet/pusa-topic-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jparmet/pusa-topic-bert") model = AutoModelForSequenceClassification.from_pretrained("jparmet/pusa-topic-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Jeffrey P commited on
Commit ·
2b857f1
1
Parent(s): 19be907
Training in progress, step 500
Browse files- pytorch_model.bin +1 -1
- runs/Jul13_18-56-35_b6a23fd570db/events.out.tfevents.1689274605.b6a23fd570db.4757.0 +2 -2
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- runs/Jul13_20-02-30_b6a23fd570db/events.out.tfevents.1689278552.b6a23fd570db.4757.2 +3 -0
- training_args.bin +1 -1
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