Instructions to use AliSaadatV/esm2-sdft-gb1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AliSaadatV/esm2-sdft-gb1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AliSaadatV/esm2-sdft-gb1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AliSaadatV/esm2-sdft-gb1") model = AutoModelForSequenceClassification.from_pretrained("AliSaadatV/esm2-sdft-gb1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 734eea73143b13208d4f0209cded9bcedb76ff5d3f27dc4cea25637138aa8c11
- Size of remote file:
- 5.33 kB
- SHA256:
- a3c6ce2fb355ebf0c9c0deb9c60ba37d701426d251628c42848d13caa7c271bf
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