Instructions to use hubentu/genemodel-bulk-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hubentu/genemodel-bulk-v0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hubentu/genemodel-bulk-v0")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hubentu/genemodel-bulk-v0") model = AutoModelForMaskedLM.from_pretrained("hubentu/genemodel-bulk-v0") - Notebooks
- Google Colab
- Kaggle
Model summary
genemodel-bulk is a pre-trained foundation model built on the Longformer framework. It has been trained on large-scale microarray and bulk RNA-Seq datasets. The model functions as an embedding tool for feature extraction and can be fine-tuned for phenotype-related regression and classification tasks.
Usage
from transformers import AutoTokenizer, AutoModel
model = AutoModel.from_pretrained('hubentu/genemodel-bulk-v0')
tokenizer = AutoTokenizer.from_pretrained('hubentu/genemodel-bulk-v0')
embd=pipeline("feature-extraction", model=model, tokenizer=tokenizer)
embd("ENSG00000169885 ENSG00000241599 ...")
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