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
Update geneformer/__init__.py
Browse filesChange init default ensembl mapping file to gc30M for time being
- geneformer/__init__.py +1 -1
geneformer/__init__.py
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@@ -4,7 +4,7 @@ from pathlib import Path
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GENE_MEDIAN_FILE = Path(__file__).parent / "gene_median_dictionary.pkl"
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TOKEN_DICTIONARY_FILE = Path(__file__).parent / "token_dictionary.pkl"
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ENSEMBL_DICTIONARY_FILE = Path(__file__).parent / "gene_name_id_dict.pkl"
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ENSEMBL_MAPPING_FILE = Path(__file__).parent / "
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from . import (
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collator_for_classification,
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GENE_MEDIAN_FILE = Path(__file__).parent / "gene_median_dictionary.pkl"
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TOKEN_DICTIONARY_FILE = Path(__file__).parent / "token_dictionary.pkl"
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ENSEMBL_DICTIONARY_FILE = Path(__file__).parent / "gene_name_id_dict.pkl"
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+
ENSEMBL_MAPPING_FILE = Path(__file__).parent / "ensembl_mapping_dict.pkl"
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from . import (
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collator_for_classification,
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