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
reinstate save_to_disk patch
Browse files- geneformer/tokenizer.py +1 -1
geneformer/tokenizer.py
CHANGED
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@@ -175,7 +175,7 @@ class TranscriptomeTokenizer:
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)
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output_path = (Path(output_directory) / output_prefix).with_suffix(".dataset")
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tokenized_dataset.save_to_disk(output_path)
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def tokenize_files(
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self, data_directory, file_format: Literal["loom", "h5ad"] = "loom"
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)
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output_path = (Path(output_directory) / output_prefix).with_suffix(".dataset")
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+
tokenized_dataset.save_to_disk(str(output_path))
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def tokenize_files(
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self, data_directory, file_format: Literal["loom", "h5ad"] = "loom"
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