Instructions to use GleghornLab/asm35_red with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GleghornLab/asm35_red with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="GleghornLab/asm35_red")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("GleghornLab/asm35_red") model = AutoModelForMaskedLM.from_pretrained("GleghornLab/asm35_red", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5108b125b6ce03a82abb97f353fb0fb7432064496a071803a360e6db1ac9e8be
- Size of remote file:
- 211 MB
- SHA256:
- 05039795dee690cf32e5c56f11ac8d8aadd6dbc7ed1be2f29b4665530b765b45
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