Instructions to use jinbo1129/try2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jinbo1129/try2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jinbo1129/try2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jinbo1129/try2") model = AutoModelForMaskedLM.from_pretrained("jinbo1129/try2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 658 Bytes
0d75654 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | from setuptools import setup
setup(
name="geneformer",
version="0.0.1",
author="Christina Theodoris",
author_email="christina.theodoris@gladstone.ucsf.edu",
description="Geneformer is a transformer model pretrained \
on a large-scale corpus of ~30 million single \
cell transcriptomes to enable context-aware \
predictions in settings with limited data in \
network biology.",
packages=["geneformer"],
include_package_data=True,
install_requires=[
"datasets",
"loompy",
"numpy",
"transformers",
],
)
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