Fill-Mask
Transformers
Safetensors
prokbert
bioinformatics
genomics
sequence embedding
genomic language models
nucleotide
dna-sequence
promoter-prediction
phage
custom_code
Instructions to use neuralbioinfo/prokbert-mini-c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neuralbioinfo/prokbert-mini-c with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="neuralbioinfo/prokbert-mini-c", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("neuralbioinfo/prokbert-mini-c", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
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license: cc-by-nc-4.0
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---
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## ProkBERT-mini-k1s1 Model
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ProkBERT-mini-k6s1 is part of the ProkBERT family of genomic language models, specifically designed for microbiome applications. This model, optimized for DNA sequence analysis. This model can provide robust and high resolution solutions.
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