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 gf-6L-30M-i2048/training_args.bin from tdc/Geneformer: direct link, hf CLI and curl.
- Browser
- Download file 2.61 kB
-
https://huggingface.co/tdc/Geneformer/resolve/1b531a57070efd45ef2d73f0e399f5ab40e5a3ea/gf-6L-30M-i2048/training_args.bin
- Command line
-
hf download hf://tdc/Geneformer@1b531a57070efd45ef2d73f0e399f5ab40e5a3ea/gf-6L-30M-i2048/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tdc/Geneformer/resolve/1b531a57070efd45ef2d73f0e399f5ab40e5a3ea/gf-6L-30M-i2048/training_args.bin
2.61 kB
- Xet hash:
- 6718ec4e7310398daadce70f1bc9eb0ee8c088af95d098f76086f08b4c7e5ef6
- Size of remote file:
- 2.61 kB
- SHA256:
- f0ec3459454205174c9d2e4d6c6930f6b0fbf3364fc03a6f4d99c4d3add2012b
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