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") - Inference
- Notebooks
- Google Colab
- Kaggle
quantization of classifier with insilico perturbation
#550
by ZYSK-huggingface - opened
Hi ,
I noticed that in the InSilicoPerturber module, both pretrained and MTL models support automatic quantization within the code. I was wondering if similar quantization is also supported for the Classifier class?
Thanks for your question. The same method would work but you should confirm the layers that are loaded with respect to the layers of the fine-tuned classifier. For example, if loaded as Pretrained it may drop the last head layer so when you select the layer to use for the embeddings “0” would be the current loaded last layer.
ctheodoris changed discussion status to closed