Text Classification
Transformers
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use afg1/pombe_curation_fold_0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use afg1/pombe_curation_fold_0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="afg1/pombe_curation_fold_0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("afg1/pombe_curation_fold_0") model = AutoModelForSequenceClassification.from_pretrained("afg1/pombe_curation_fold_0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a881287bd00c3acaddc0a125c371b300cfb05550e8cd41e74db3dbdfa070cdc
- Size of remote file:
- 5.18 kB
- SHA256:
- d9269586ff399e1705bc6562ca89d47b9be4ebde61b67e8dd79285b6d1afc973
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