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")# pip install -U transformers accelerate # 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
Download geneformer/__init__.py from ctheodoris/Geneformer: direct link, hf CLI and curl.
- Browser
- Download file 558 Bytes
-
https://huggingface.co/ctheodoris/Geneformer/resolve/c48e37c67945c09e6593d45c40c4cbe0df7cc757/geneformer/__init__.py
- Command line
-
hf download hf://ctheodoris/Geneformer@c48e37c67945c09e6593d45c40c4cbe0df7cc757/geneformer/__init__.py
-
curl -L -o __init__.py https://huggingface.co/ctheodoris/Geneformer/resolve/c48e37c67945c09e6593d45c40c4cbe0df7cc757/geneformer/__init__.py
558 Bytes
| from . import tokenizer | |
| from . import pretrainer | |
| from . import collator_for_classification | |
| from . import in_silico_perturber | |
| from . import in_silico_perturber_stats | |
| from .tokenizer import TranscriptomeTokenizer | |
| from .pretrainer import GeneformerPretrainer | |
| from .collator_for_classification import DataCollatorForGeneClassification | |
| from .collator_for_classification import DataCollatorForCellClassification | |
| from .emb_extractor import EmbExtractor | |
| from .in_silico_perturber import InSilicoPerturber | |
| from .in_silico_perturber_stats import InSilicoPerturberStats |