Instructions to use knowledgator/SMILES-DeBERTa-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use knowledgator/SMILES-DeBERTa-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="knowledgator/SMILES-DeBERTa-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("knowledgator/SMILES-DeBERTa-base") model = AutoModelForMaskedLM.from_pretrained("knowledgator/SMILES-DeBERTa-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from knowledgator/SMILES-DeBERTa-base: direct link, hf CLI and curl.
- Browser
- Download file 139 MB
-
https://huggingface.co/knowledgator/SMILES-DeBERTa-base/resolve/main/optimizer.pt
- Command line
-
hf download hf://knowledgator/SMILES-DeBERTa-base/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/knowledgator/SMILES-DeBERTa-base/resolve/main/optimizer.pt
139 MB
- Xet hash:
- 52b53567e5dc4e85bee7dd8648e621fa582134e7c0936bf93a8b9d718936d734
- Size of remote file:
- 139 MB
- SHA256:
- 0fcfa92fb8047f2f7c2600898a956eceba49881db5380fd77a87f89cb90849fa
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