Instructions to use jaykmr/ESMCrystal_t12_35M_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jaykmr/ESMCrystal_t12_35M_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jaykmr/ESMCrystal_t12_35M_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jaykmr/ESMCrystal_t12_35M_v2") model = AutoModelForSequenceClassification.from_pretrained("jaykmr/ESMCrystal_t12_35M_v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 28a8f28cf2c2ed7843668ea5c163bca89bcedae76e3c7361d8222ffa2af68e4c
- Size of remote file:
- 136 MB
- SHA256:
- 91c69d30b01d07ade78007f1adaad12c745736f01d3250c407cb1ab07362fcaf
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