Instructions to use JFoz/esm2_t12_35M_UR50D-finetuned-localization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JFoz/esm2_t12_35M_UR50D-finetuned-localization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JFoz/esm2_t12_35M_UR50D-finetuned-localization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JFoz/esm2_t12_35M_UR50D-finetuned-localization") model = AutoModelForSequenceClassification.from_pretrained("JFoz/esm2_t12_35M_UR50D-finetuned-localization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7dbef0faf0cf64b5ca9d34d0816766fa91ff7e0f80cf73660f790ea8c7994966
- Size of remote file:
- 136 MB
- SHA256:
- 7ebe5c1b0e95d3338d5b34525c6f5a2d96484218bf263caca7c72aa0852ce462
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