Instructions to use tdc/Geneformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tdc/Geneformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tdc/Geneformer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tdc/Geneformer") model = AutoModelForMaskedLM.from_pretrained("tdc/Geneformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from tdc/Geneformer: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/tdc/Geneformer/resolve/main/training_args.bin
- Command line
-
hf download hf://tdc/Geneformer/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tdc/Geneformer/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- 55b0084622483acf59af0890dccf4f90ae3b055dc102d5d0fc2081e860fb4e1b
- Size of remote file:
- 5.05 kB
- SHA256:
- 5afed602918d6f0c4916c1b9335bcdb619bca2c6fd6c7e0dd2a86d195264b8cc
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