Instructions to use ctheodoris/Geneformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ctheodoris/Geneformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ctheodoris/Geneformer")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ctheodoris/Geneformer") model = AutoModelForMaskedLM.from_pretrained("ctheodoris/Geneformer", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Use dynamic CUDA check instead of hardcoded device in emb_extractor.py
Fixes CPU-only inference, which currently fails with "AssertionError: Torch not compiled with CUDA enabled" because device="cuda" is hardcoded.
Replaces the hardcoded "cuda" with a dynamic check ("cuda" if torch.cuda.is_available() else "cpu"), matching the pattern already used elsewhere in the codebase (e.g. perturber_utils.py line 194).
See discussion #592: https://huggingface.co/ctheodoris/Geneformer/discussions/592
Thank you - I think input_ids was inadvertently overwritten in the forward pass so I just reinstated that and moved the device check to be outside the loop so it only does it once. Please test to make sure this works and let us know if any other issues arise. Thank you for your contribution to the codebase!